I worked for a large e-commerce company. I wanted to investigate putting all our support data into Watson and see what sort of recommendations it could provide, maybe a sort of auto-suggestion to help our customers. Three really funny points stand out from the experience:
1) To apply for Watson access you needed to show C-level approval, so our CEO put his name and phone number on the application (trying Watson was somewhat his idea). A few months later, an IBM marketing team called HIS CELL and asked for ME. Imagine how it felt to have the CEO walk up to me, deadpan hand me his personal iphone and say "It's for you."..
2) They told me they'd help me with the support data idea, and every meeting we set up they tried to pitch "what if we put Watson on all of your customer's storefronts, we could add a 'powered by watson' banner on every page, and you give us a cut of GMV?". I pivoted them to our plugin framework and told them to build it themselves.
3) To demo the technology, the first step was to buy a $250k server from IBM. To demo it.
IBM is famous for charging people for the privilege of talking to them, even if you're trying to sell them something.
This strategy makes sense if you consider that even in it's heyday Watson was 95% data science consulting firm and 5% actual valuable technology.
I really think Watson is one of the biggest tech marketing bamboozles of the 21st century. Through Jeopardy they really had a segment of the business world and the general public convinced that they had cracked AI, but behind the scenes it was all one-off custom solutions under one trademark.
I think maybe the common problem is that there’s a hidden and false assumption that being good in one domain will transfer elsewhere, it doesn’t and didn’t
The Jeopardy thing was pretty brilliant in a sense - wrangling an episode of free advertising from one of the most popular game shows. A memorable episode at that!
AI/ML has somewhat continuous research going all the way back to the First AI/ML Boom of the 1960s and the Second AI/ML Boom era of the "Lisp Machines" [1] in the 1980s. Depending on who you ask the current AI/ML Boom is something like third or fourth wave, and yeah some of that depends on where you fit Deep Blue and/or Watson in the timelines (or even if you bother at all to count them, given all the other comments here on how Deep Blue/Watson have always been PR maneuvers more strongly than technical lines in the sand).
Deep Blue isn't ML at all, it's just a purpose built system for solving chess. It doesn't learn anything as such and just a fancy brute forcing machine that (smartly) goes through all possible chess moves and selects the best possible tree of outcomes. The work on actual ML happened independently of this.
That is a form of machine learning. It uses an algorithm with an enormous ability to look ahead, and selects the moves according to a heuristic that have been shown previously to be most likely to create the desired end state.
Chess is not a solved game from the starting state, so it has to make assumptions based on the data it has. This is machine learning.
Please don't make such definite statements. You even say it in your own comment "selects the best possible true of outcomes", how do you think it selects this? It uses heuristics to assign values to different board states, and in the case of Deep Blue these values were created through previous game analysis. If a knight to c2 on turn 8 is rarely seen in the same game as a winning board state, then this is valued lower.
Looking through the tree wasn't the ML part, but knowing how to pick the best node on the tree was.
Deep Blue is ML.
> It uses heuristics to assign values to different board states, and in the case of Deep Blue these values were created through previous game analysis.
Unless I’m misinformed, this part isn’t true. The heuristic was hardcoded with the help of human experts.
From the paper Deep Blue by Murray Campbell et al (people who worked on Deep Blue)
"The initialization of the feature values is done by the “evaluation function generator”, a
sub-program which was run on the master node of SP system." Which would suggest it generated the heuristic itself. The features may have been hardcoded, but assigning values to them wasn't.
In addition to this, feature values could be static or dynamic, meaning it would update dynamic ones depending on the board state. It not only generated the heuristic values (feature values) it could modify them to reflect their relative change in impact throughout the game.
Deep Blue and Watson aren’t the same thing. Deep Blue was a chess computer from the 90s — and it was not the first chess computer, so regardless of whether you consider computer chess to be part of AI, the answer is no.
They bamboozled no one who knew anything. Even the "sold off in parts" bit in the OP article title doesn't surprise anyone who knows what "Watson Health" means. It was never a platform just a bunch of disjoint garbage components. You couldn't sell the platform so now they're selling off the tools. Imagine a toolbox with a spade a fork lift and a soldering iron.
Watson is one the greatest marketing achievements of the 21st century.
It’s literally consulting with open source software. But they packaged it up in an attractive format that got them buzz. Imagine what that marketing team could do for a product that was able to half work!!!
Ehh...I get why tech people are suspect of Palantir but they're just disrupting other government contractors.
And from my limited experience working with the government, they absolutely need / want / rely on having companies hold their hand as they insist on doing things the hard, slow, and very custom way.
I feel like with this comment, the word "disrupting" has officially jumped shark and lost any and all meaning.
Palantir isn't "disrupting" government contractors. It is a government contractor, țhe old-fashioned kind, at that, and nothing more.
And people aren't suspect of Palantir. People dislike Palantir because its government contracts are shady and boring (they're all about efficiently tracking people), but they pretend to be a "saving the world with tech" startup with such enthusiasm you'd think they put the Kool-Aid into the water coolers.
Unsurprisingly, XXI century Stasi trying to look hip to recruit the tech talent give off nothing but "how do you do, fellow kids" kind of vibes.
Disclaimer: interviewed for Palantir. They thought I could be a fit. Must have not been using their own software to vet candidates back then.
To be honest, my experience of private enterprise is that they insist on doing things hard, slow and very custom. Almost every problem that exists is distinct enough that you can argue it doesn't fit the existing COTS software. It's sometimes necesary to build something yourself, but no where near as often as it is done.
If I remember correctly, John Ralston Saul made the point [0] that there is little observed difference in terms of the efficiency of decision making between large government and large corporations.
My personal experience is that large organisations and government are barely distinguishable. This is often excused in the name of "risk mitigation" - but in my experience it's really just that there are more snouts in the money trough, and that politics is more important than success. The close ties between government and the largest organisations also invite a similar culture.
The end result for both government and large enterprise is "hard, slow and very custom". (Of course, there are exceptions in both government and enterprise).
Some might do it under the belief that it makes them more flexible later on, but going with off the shelf stuff means it's easier to find people to create and migrate to a custom system when or if it's needed.
Disrupting? Their stock price has dropped by two thirds from its peak. They're probably looking to find a buyer at this point, such as IBM itself, while the leadership uses them as a stock-printing machine to enrich themselves.
Doesn’t this apply to most startups though? The core technical problems aren’t “hard” it’s that the industry involve can’t adapt due to inertia of entrenched companies.
>Karp has described himself as a socialist and a progressive, and said he voted for Hillary Clinton. In 2017, he was recorded during a Palantir company meeting claiming he turned down an invitation from President Trump, saying “I respect nothing about the dude.”
>He has said that technology companies like Palantir have an obligation to support the U.S. military. He has defended Palantir's contract with U.S. Immigration and Customs Enforcement during the controversy over family separations, saying that while separations are "a really tough, complex, jarring moral issue," he favors "a fair but rigorous immigration policy". He has said the U.S. government should have a strong hand in tech regulation and that western countries should dominate AI research.
>Karp founded the London-based money management firm Caedmon Group.
>In 2004, along with Peter Thiel (who had been a classmate at Stanford) and others, he co-founded Palantir as CEO.
>He is described as a wellness fanatic who swims, skis cross country, practices Qigong meditation and martial arts, and keeps Tai Chi swords in his offices.
He'd make for a good Silicon Valley or Black Mirror character.
IBM, Oracle, Panatir....in a lot of cases these are pro services companies that custom build whatever is needed. LOTS of money in enterprise application development.
Consultancy + adaptable software is a decent business model. Unfortunately "adaptable software" for {insert industry} is a really hard target to architect right.
Especially when the majority of your tech headcount bills by the hour and gets paid to tell the customer "Yes."
That's how it is for just about any non-trivial business system. They're sold as complete systems, but there's still customization required for those systems to actually fit the business - and it's through offering consulting for those customizations that enterprise software vendors make the big bucks.
Not really assuming they are the prime contractor all the value is in the contracts and those are time limited before being re-competed lose all your contracts and your business value goes to zero because there is no IP like a Google or a Microsoft would have that is at the core of the value of the company.
Who thinks that? I've never heard this. People thought Watson was a lot more capable than it actually was just because of the Jeopardy PR stunt. People outside tech were buzzing about IBM and Watson. In my experience, people outside tech barely know Palantir exists.
The company I worked for used some Oracle tech and I was trying to get some high level information about a product but their website kept requesting my e-mail just to show me some documentation.
Once I provided them with my e-mail, I started receiving "You must take us to your leader" messages in a tone as if I was their employee and they were commanding me to take them to my CEO. I can't imagine myself chasing the CEO in the building because some sales people in Oracle told me to do so :)
To be fair, after being in meetings with theirs sales engineers(who wore the best shirts I've ever seen) a few times I grew to respect their stubbornness and the way they structured their corporate machine. It's a valuable lesson to have an exposure to corporate dealings I believe, before that I used to do freelance stuff and had no idea how a simple webpage can cost millions and why a large corporation won't buy that easily from a small company with similar or better product at the fraction of the cost.
IBM along a few other behemots pitched for a serious project at a company I worked for as enterprise arch. All companies brought their top salespeople, and all tried nasty things, but IBM was by far the worst. Their top guy started their pitch by saying he chatted with our CEO over the christmas holidays. He mentioned - and I am not making this up - that he should be talking to people higher in the org. (The most junior person in the room was me, the rest were board-2/-3s). It soon emerged their thing could not work, and I killed it in the first round of pitching. What followed was my bosses' boss, the CIO of a very large company, called me and gave me an earfull since he himself has to explain to CEO why we had the audacity to not choose IBM.
I'd not touch anything IBM ever. Bunch of assholes.
Yup - I had the same "your guy is a problem, he's anti-innovation." The brilliant thing was that they rang the CEO of the business unit who was at that time +4 on me and had never met me. He was flummoxed and invited me for lunch to find out how I'd made such a big impression! Did me loads of good!
It's because they want to talk to the most power in the decision but with the least information as to how the problem could be solved without the help of Oracle/IBM/whoever.
This, 100%. Think about it another way: IBM et al. sales only lose by talking to lower-title folks.
Best case, they lose control of the narrative as it's reported up internally, and someone higher up still has to approve it.
Worst case, some engineer who actually knows their shit very quickly outlines why this can never work for the given problem.
Once you're into the VP level, there's (usually) less technical knowledge, because folks at that level have full days crammed with higher-level decisions. So it's more plausible for sales to pitch {insert whatever buzzwordy, batshit crazy idea} and have it fly.
To add on, it's also a standard negotiation tactic for a negotiator to try and speak to the highest-ranking person possible. This tactic was specifically recommended by a guest speaker at a Stanford Business School seminar about how to negotiate uploaded to YouTube (timestamped to 31:59 for the relevant bit). [0]
Yep. I used to do technical sales support. I would come in after the sales manager had broken the ice and arranged for some of the customer's technical team to listen to our proposed solution. But the sales training we got told us to always sell at the highest level possible, preferably the person who would sign the purchase order, not lower level technical people.
That didn't always work out. We sold a lot of stuff to Hewlett-Packard and they always forced most of the decisions down to the engineers. They would rarely let us talk to the people who could sign the purchase order. The sales people didn't like it much since they didn't have the control that they were used to. But it was kind of great for all of us technical people because we could sit around with the HP engineers and talk about technical stuff without a lot of sales-speak getting in the way.
But wouldn't a competent VP, C-level just shrug and say 'I want technical approval first from my teams, we don't do favorites here, my time is precious and you're making me lose precious amount of it? I had a business unit manager answer that to such queries that way and it felt like good management... Isn't the whole shtick about management to be able to delegate and trust your org?
The quote I mentioned is just a quote, but it points to a part of a reason. If you are a CEO or a high level executive of a big company, going with IBM or Oracle is a safe bet. It's not very likely you will be blamed for failures of IBM or Oracle. It may be a money hole and bad for business but it's a much safer bet than going with some smaller vendor instead of big name vendors.
The "nobody got fired for buying IBM" thing expired decades ago, that mantle passed on to Microsoft. Last 5 - 10 years, nobody gets fired for architecting dozens of microservices in the cloud.
One would think the decision makers would trust the technical advice of the smart people they've hired instead of the opinion of some obviously lying salesman...
Yeah except that a lot of - not all - executives maintain something akin to class solidarity with other executives at big companies, especially their big vendors..
Because at some point they might want/need another job, and so often times it's better to help each other out, at the expense of the folks lower down.
Those folks are useless to them, personally, but that VP at Big Vendor probably isn't.
Considering that the buzzword shooting, smooth talking sales rep offering an easy to solution to, well, all of the problems is much closer to how most C-Level guys (in established companies at least) think, I'm not surprised anymore. This till manages to chock me from time to time, so.
> Their top guy started their pitch by saying he chatted with our CEO over the christmas holidays.
I had a former Oracle employee use a similar line in an interview for a software engineer position. After repeatedly refusing to answer technical questions then admitting they hadn't written software in over a decade:
"I'm actually good friends with someone high up in Company."
You perfectly demonstrated why they shouldn’t be speaking to you. Their schtick is crafted to work on levels where you don’t get to tank the deal until it’s way too late and egos are now on the line.
"Nobody ever got fired for buying IBM" was the common phrase at our company in the 1990s. At the time, that was certainly true. Which lead to adoption of truly awful tech, token-ring over type-1 cable, versus ethernet over twisted pair.
I was involved in a small project, and we were running low on the money runway for next phase. The IBM sales guy literally barged into a FORTUNE 50 CIOs office, without an appointment, asking for budget to be approved for the next phase. project continued, but I never saw the sales guy again. The team had a good chuckle and I never understood what the guy was thinking he would achieve with this tactic.
IMHO that is like kids and lying. More often than not, the right answer to the question "Why are you doing this, when we always catch you?" is "Because it works more often than you catching me lying and also because you don't even get that".
Well, no. In the end they backed my reco and we didnt go IBM. I feel like I did inconvenience my managers though, and indeed left not long afterwards for a better job.
My first Oracle experience was similar. Back in the 90s, I was tasked with replacing our old mssql6.5 generic custom built rack log server with something stronger as the product was successful and we had money.
Oracle put me in touch with their eval solutions people who took all my info on number of users, transactions, size, etc and came back with an estimate of a $2M Sun+Oracle box. I told them that the current solution ran on like $10k of licenses and hardware and they revised the spec down to $250k.
They were totally clueless but projected absolute competence.
Unfortunately, still don't know what you're talking about. Probably because I don't have expertise in the area. Am imaging some kind of white-collar business shirt that's... platinum plated? If the design is not extravagant, how would anyone know?
Nothing exotic but extremely good quality and attention to details that you can recognise from distance. No button looks off the shelf, no detail is cheap out. The cut matches the body perfectly and elegantly and the designer and manufacturer definitely went the extra mile even if it wasn't the easiest or cheapest thing to do. Maybe cutting in straight lines would be the easiest way to do it but if the design requires a slight curve, they wouldn't shy away from it. The more you look at it the more details you notice that someone must have agonised over it even if it wouldn't make any functional difference. Just because it's not visible all the time, doesn't mean that can't have a nice design, for example inside the collar has also a seperate design.
To expand on this, because I think some of the confusion is probably from more basic concepts...
Clothing patterns, stitching, and details differ in manufacturing time and suitability for mass production.
The vast majority of clothing is optimized for production, because time is expense, and therefore less time is more profit.
In men's sizing, we generally come in fewer shapes. Square-to-athletic-to-slim fit + arm length + overall size.
But for most people, there's still going to be a delta between {hypothetical optimal fit} and {nearest mass-market fit}. So a nice shirt really starts at doing whatever it takes to get closer to optimal fit (even if it requires some difficult, hand-sewn-only magic) and adds better materials and finishes (buttons, button-holes, stitching, etc).
At the end of the day, it's kind of like watches though -- 95% of people won't recognize the differences. I got more complements from C-level folks on my $50 quartz Casio diver [0], because it copies a lot of Rolex details, than anything mechanical without plastic.
Oh, it is much better than a $10 shirt but its utility doesn't come from it's comfort or purely aesthetics IMHO.
Maybe it's silly but people do judge from appearance because it tells something about you. I have been watching this famous fashion photographer and he was talking about using an iPhone for last photoshoot and he noted that he can do it and charge full price for it only because he already has a name in the industry and a nobody will need to flash large and expensive cameras to justify the price asked.
Think what it it tells about you to wear really nice shirt. Firstly, it implies that you already sold something to someone for a lot of money and you got paid and bought that shirt, right? Secondly it implies dominance at least in one area, you are the person with the best shirt in the room so who knows what else you are best at. Silly but our primate brains easily get intimidated and extrapolate. There are also many other fallacies that our brains easily fall in, so looking impressive is a superpower actually.
Also, everything is a costume. If you are interviewing for a nerdy position you better look like a nerd but you can always be the nerd with the best nerdy shirt.
The nerd costume is a costume too. If I'm wearing a t-shirt and a battered hoodie in a meeting with a bunch of suits, then everyone is going to defer to me on technical matters
I have multiple articles of clothing that cost more than that. I’m baffled as to why anyone would want a keyboard that costs more than $100. To each his own.
Keyboards that cost over $100 tend to be much, much nicer, and are more easily tailored to an individual's taste.
Around $200 and above, most are machined from aluminum, and require the user to supply their own switches and keycaps. My daily driver, whose USB connector seems to be reaching EOL, is a heavy-ass chunk of bright blue Alu, makes noise like a machine gun when I need to correct someone on the internet, and has limited edition keycaps in a fun (imo) purple-and-cyan color scheme. Total cost of this thing was probably $250~$300, but I'm happy.
I have over $1k worth of keyboards and related hardware strewn about my apartment, and the only reason I've considered selling some of my collection is to buy fancier pieces. To each their own.
The keyboardio keyboard I'm typing on (A Model 1) puts substantially less stress on my hands and wrists than any other keyboard I've used. As someone who has had repetitive stress pain in my wrists, I consider it - well, not beyond price, but certainly worth a few hundred dollars when it avoids surgery and enables me to pursue a HIGHLY lucrative profession full time. Each person's hands are different, so maybe you do fine with an inexpensive keyboard, and my keyboard won't suit everyone, but it's a fairly straightforward explanation the way I see it.
A crisp, blinding white, heavy oxford cotton shirt that requires cufflinks is noticed by everybody but nerds. In financial circles you can even wear colored shirts but don't stray from blue or pink.
The people who wear those shirts also have expensive shoes. Get the tie right and you can get away with a slightly less expensive suit for technical sales meetings.
A clean shave and neat, well cut hair help too.
Its interesting to look at shoes, tells you a lot about a persons status in a big organisation.
Having said that, my daughter bought me some checkerboard vans so I wear those everywhere now.
Aren't shirts in that range having diminshing returns? like couldn't get a $100 shirt that covers most of the benefits? there has to be a optimal local maximum there right?
Not if you’re in sales, I’d guess. It almost literally tells your target C-suite that you’re cut from the same cloth and to ignore the bleating of underlings. It’s a peripheral cue calibrated to increase bonding and trust. “These are my people. I’m safe with them.”
I guess it's sortof like going into a "hackers" convention and seeing people typing on a 3$ Dell keyboard. Those are not our people. However, the guys in the corner with DasKeyboard or Happy Hacking Keyboard; those ARE our people.
>1) To apply for Watson access you needed to show C-level approval, so our CEO put his name and phone number on the application (trying Watson was somewhat his idea). A few months later, an IBM marketing team called HIS CELL and asked for ME. Imagine how it felt to have the CEO walk up to me, deadpan hand me his personal iphone and say "It's for you."..
This sounds like the biggest power move you could ever pull.
Everything about this sounds like they hired inexperienced sales people and promised them huge payouts if they could close certain deals. The kinds of sales people who won’t hesitate to burn a lot of customer relationships to the ground as long as they could close a few big deals for themselves.
Wow, I can't believe how accurate this story is, same thing happened to me I think summer 2016 but I thought it was because our execs were idiots not that IBM would treat every company like that... CTO calling me to his office to talk to IBM on their personal phone, he was the only one who wanted Watson (this was a healthcare company, I was VP of Eng). And yes, they were obsessed with putting their logo everywhere, and as soon as we heard it was so expensive, we had to tell our CTO to chill, we stopped, cause you know you can hire at least 2 devs for that money.
I concur with the experience of dealing with IBM sales.
Years ago my client wanted me to checkout out IBM mobile app builder - Worklight, The pricing wasn't available on website and so I had to contact them. Soon I was reached out by their sales department and before I could get any details on the pricing I was speaking with VP of sales.
If I remember it correctly, It was priced ~>150K USD and even after repeatedly telling the VP that I was just exploring what their product was, The VP told me he was ready to fly in to my office the same week to 'talk further'. It was weird to end that conversation with them and my client had a good laugh when I shared the experience.
I don't get why IBM finds it hard to deal with Startups, All other behemoths (MS/Amazon/Google etc.) have successfully created products for Startups often by offering generous freebies and 'Pay as you go' plans . Where as IBM still thinks they can slap Fortune 500 pricing on entry-level startups.
I guess as long as those Fortune 500 companies & even Govt. fall for that Watson type products, They don't have a reason to change.
IBM don't want to deal with startups. They need big, old, ossified, cashed up businesses who are in some kind of trouble. There isn't any money in most startups that bootstrapped off a pile of open source or free tech.
Startups are more likely to see through the bullshit. It's similar to why spam emails often have intentional spelling mistakes - to get the marks to self-select.
> an IBM marketing team called HIS CELL and asked for ME.
What the fuck is this? A name/email for your company when trying something out is so that you can keep track of any support requests we need, not for you to sell shit to me.
Yeah, the whole culture there (and other places like Oracle) is all about implanting mindshare at the decision-maker level and driving unilateral adoption from the top down. Pursuing such an approach is highly revealing because if the technology actually worked, that approach would not be necessary.
Once they’re “in” at the decision-maker level, they can continue to milk the organisation with long-duration support and consulting contracts, feeding parasitically and gradually becoming more and more entangled.
Oh yeah I worked on a similar project at Oracle. The sales people basically sold the state on a 'stack' with a bunch of random horseshit that was magically supposed to work together and then dumped it on engineering. I mean that in a totally serious way, sales seemingly just grabbed a bunch of names of Oracle software and mashed it together. It literally never worked at any point.
I met one of the "managers" on that who told me with a straight face "All you need is a college degree in anything to manage developers" (hers was in English IIRC)
> Pursuing such an approach is highly revealing because if the technology actually worked, that approach would not be necessary.
This is, sadly, untrue. Enterprise reps do this because on the whole, it doesn't matter if you have the best technology - if the other guy is successful at the CxO level, the customer will go their way.
> Once they’re “in” at the decision-maker level, they can continue to milk the organisation with long-duration support and consulting contracts, feeding parasitically and gradually becoming more and more entangled.
IBM seems like a really interesting case study in parasitism at the organisational level. Just moving around, feeding from host to host. I wonder if anyone’s studied it in those terms.
Marketers have no sense of boundaries or limits. Everything they do is in violation of social norms. You give them an email that's clearly for some specific and useful purpose, they abuse it by turning it into their personal marketing channel which benefits nobody but them.
In my experience this seems to be a theme with very senior executives - they are very often interested in snake oil and can’t seem to discern snake oil from real medicine.
This reminded me of my experience with them a few years back with MQTT. They were pushing their Bluemix/cloud hard and I just wanted to test it out. Never again.
It used to be you can't get fired for hiring big blue. In the end it was always a lot of sales /pre sales folks, and a lot of substandard subcontractors milking the golden cow. I don't miss managing their implementations/deliveries at all.
I worked at IBM Watson as one of the early engineers when they first started commercializing the product. It was a fucking joke - Ginni Rometty would go up on stage and said that Watson can help diagnose cancer from CT scans and we would just look at each other and be like "Dude, Watson is just a glorified Lucene index, wtf is she talking about." They started selling Watson as the end-all for everything from cancer diagnosis to customer service chat - they even had a stupid Watson Chef thing at SXSW one year - but none of that used the original Watson codebase - it was all built from the ground up and lots of it was just simple logistic regression
> they even had a stupid Watson chef thing at SXSW one year
I loved Chef Watson, am sad that it's gone, and would pay a small amount for renewed access.
It wasn't "smart", and its recommendations needed to be tempered with human understanding, but I wound up with some great recipes that I wouldn't have thought of otherwise.
I think the best was goat milk mac & cheese with radishes and red miso.
The funniest was when it told me to remove the connective tissue from tofu.
I worked on Chef Watson and was part of the team at SXSW. One of the most amusing parts was how much it loved bacon. This was because bacon could be sweet, savory, salty, and fatty - it all depended on how you cooked it. A big part of the way that Chef Watson created recipes was by connecting flavors together. There was a while when it didn’t record why it had included an ingredient - so bacon would be brought originally because it can be sweet, but then it would immediately bridge to the fatty flavor. Fun times indeed.
I worked for IBM (non-Watson) not too many years ago and this cracks me up because I heard the same from Watson employees I spoke with. And it wasn't just Watson that Ginni talked fluff about. I swear every word that came out of her mouth was a combination of fluff and technical buzz words. We all used to sit around a workstation when she would give her monthly talks and ask one another what she was talking about, because none of us had a clue. IBM seems to encourage that fluffy, buzz word exec talk, and to be honest if I hear someone talk like this now my mind turns off.
One of my favorite past-times is talking with loyal IBM employees and seeing if they can tell me what Watson is, does, or how to use it. Ginni is laughing all the way to the bank at this point so I guess the joke's on us.
As someone doing a CS degree now, I seem to be the only one who doesn't want to have anything on my resume to do with "AI", blockchain, ML, NFT, chatbots, etc... all I see is overhyped product after product, one-size-fits all solutions that frustrate customers and create problems for humans to clean up, hugely valued companies that have very little real improvement over conventional technology, etc.
An "AI chatbot" is far inferior to a real user interface. A real user interface allows discoverability (looking through menus to notice functions that may be useful later), experimentation, and puts the user in control of the program.
For example, my bank apparently only supports viewing the reason for card declines through the chatbot--something I never knew, because I took the time to go through the menus when I first got the app and learn what functions existed.
Since you're still a student, I feel like maybe I can offer some advice:
First, I think you're getting the wrong lesson from this. The key takeaway is stay to away from IBM. Almost everyone in the field has known that Watson is a bunch of marketing hype since day one. It's no surprise that Watson Health didn't work out. That doesn't mean that everything is overhyped, and it's important to develop a good sense for what is and what isn't when deciding where to work.
Second, every technology looks stupid when it's new. Airplanes, computers, the Internet, mobile phones -- they all had drawbacks that made them vastly inferior to the alternatives for most tasks for the first years/decades of their existence. It takes a lot of iteration and improvement to make something that's useful for everyone. Chatbots will probably get there some day - but it will take some big improvements in NLP. Perhaps this is the time to be working on them since we have a good idea of what we'd like them to do, and we just need to solve the challenges to get there.
Finally, realize that you're not the typical user. I doubt if very many people take the time to go through the menus like you did.
I agree with morpheuskafka, and I'm almost a couple decades out of college. The industry values buzzwords over actual product. It's embarrassing, if you take the time to think about it. It reminds me of a cargo cult. Maybe if we just throw some blockchain big data AI up, the market will reward us with its riches. The most transformative companies value product over any specific technology. They try to solve the customer's "jobs to be done" by any means necessary, often using tech that is not particularly sexy.
> Chatbots will probably get there some day - but it will take some big improvements in NLP.
They write copied platitudes, they will follow their checklist no matter what, they will usually not help at all except for wasting time and they hardly speak your language. Honestly, they emulate first level support quite well already.
I don't think NLP is the problem here. Even if you crack NLP perfectly and would somehow be able to build a semantic map, or whatever your technology would use, of the user request with perfect fidelity, there's still the question of actually understanding what it's about. Perfect NLP would help in very limited number of situation where the meaning is clear - i.e. doing some pre-defined action, like closing an account or telling the balance. But somebody comes with a request like "my dog ate my credit card, so I by mistake used my debit one and it resulted in overdraft and penalty change, can I have that reversed and get a new one?" and I'm pretty sure chatbot won't be able to handle it, NLP or not.
> there's still the question of actually understanding what it's about.
Philosophically interesting, but in practice entirely unimportant. What you want is something that speaks like a human would speak in a similar environment, then the issue (getting the correct responses) is solved. Whether or not it actually understands won't change a thing about that situation.
Speaking nonsense like a human - i.e. being a perfect simulation of a mentally deficient human - is not going to help much. If you would respond with perfectly grammatical sentences bearing to relation to the question in hand, at best what you'd get would be Elisa (granted, 90% of tech support may be that), at worst, it'd be pissing off the clients.
If you want to do something less buzzwordy with lots of real-life applications, look into distributed systems. Try running an Apache big data project yourself and write some programs/queries for it, try making a change to the project to do something cool. My suggestion to check out an Apache big data project is just that it gives you a good place to learn, not so you can be a "hadoop specialist" or anything like that.
There is way more real world usage of the distributed systems concepts and skills you'd learn there (especially in large tech companies) than any other flavor of the month. While ML is also commonly used in the industry, the signal:noise is really bad, because a lot of its uses are superfluous buzzword-driven development. However, many many companies rely on distributed systems to be able to operate at scale.
Absolutely. I often joke that my work as a data scientist is mostly creating bar graphs for people. The actual analysis is often reasonably simple, its the aggregating of the data that is hard (its messy, its not all in the one spot and there is lots of it).
So start with querying your big data to say what the top three event types are. Then slowly crank up the analysis complexity, but not too much. The data engineering has lots of scope for real solid and obvious applications.
Big data tools are just one example of distributed systems. I suggested looking into them because there are a lot of open source ones you can play with, not because I think big data isn't a buzzword (though Spark is definitely used a lot in industry).
Crypto is of course a distributed system too (at least, many are) but in practice it's a bit different than anything you'd see in industry because it's trustless.
I agree that they are novel and interesting to learn, but practically speaking, the person's point, is they are over hyped, and honestly since most use cases popping up aren't decentralized or are decentralized, but being regulated by a centralized party, like a government, it seems that they are the most inefficient way to run a distributed system.
+ People care about what other people are talking about. They like to fit in, like they're part of the cutting-edge.
+ Less experienced people have less…experience with the downsides of what they're reading about.
+ CS is no longer mostly people who care about computer science, in the same way that economics isn't only for people who want the understand economics. Tech salaries — especially engineers' — are super high, like investment bankers. So people study the respective fields as a means to an end.
+ Twitter is driven by VCs, tech press, and people marketing themselves. They're work themselves into circular frenzies all the time. Little of it matters. Almost none of them have any record of predicting what's next and a long, long record of being wrong. This is true of most people! But these are the spaces many people look to to see what is "wanted".
You seem to have good instincts. Don't be distracted by peers who work at "hot" startups or big named companies. Find something you believe should actually exist in the world and work on that. It will give you an intrinsic reward that money can't buy and status can't fill.
> CS is no longer mostly people who care about computer science, in the same way that economics isn't only for people who want the understand economics.
That's the main reason I decided against a CS major even though I love the subject. It's just disheartening listening to discount business majors butcher even simple technical topics. The pure math track actually has more than a few people in the same situation, so I wound up meeting some enthusiasts anyway.
These people may be majoring in CS, but there's really no way around it in the end - to be successful in this field, you have to really love computers. Unless you're a certifiable genius, part of the challenge of this field is just spending a ton of time in front of the computer, learning all the little things. This is a lifelong journey, one that's impossible to complete, and one you can't fake or BS your way through. I don't think CS is a bad major, it's still extremely marketable, but you just have to recognize that this is just one piece of the puzzle for the top jobs, and the other piece is technical prowess, a skill you really have to grind to get good at.
On the other hand, jumping aboard the hype train can be a good way to make some money without much skill. Might not be as fulfilling work, but it shouldn't be discounted.
Sorry but you're wrong, all those buzzwords have their merit and there are real impressive and innovative companies or projects built on those hypes, not all is "worthless" or a "scam". Don't let your ignorance blur your mind, learn about them, use them, have your own ideas cause this post sounds like you've been reading way too much HN.
> An "AI chatbot" is far inferior to a real user interface.
That's because you're lucky. You have good enough sight and you can use your hands. Unfortunately, that's not the case for millions of people especially since our populations are aging more.
I'm curious about your response here, as I'm certain that I'm missing something. I have cerebral palsy, which comes with issues using my hands. I've also had noticeable degradation with age of my eye-sight over the past couple of years. That said, I'm not sure how a chatbot helps people with these issues. Typing multiple sentences into the chatbot interface is certainly more tiring and error prone that click a few buttons. Similarly, reading multiple lines of minuscule text in a chatbot window is more eye strain than a couple of menus with large text (the larger text being possible since less words need to fit on the screen).
As a developer, I care about accessibility issues. Given your statements, there's obviously a gaping blind spot in how I'm thinking about these issues. Could you elaborate a bit more on the topic?
Alexa, Siri, and Google Home are essentially AI chat bots using microphones. The former two can barely process anything you ask but you can still get a lot done with them.
Searching movies to watch with Alexa works better than with the clumsy TV keyboard. I think for some applications or some people chatbots may be better than traditional UIs. Also they should be getting better over time.
Most solutions to real-world problems offer tons of deliciously complicated CS issues to chew through.
Just find problems to solve that are interesting to you, hype is irrelevant in finding a worthwhile thing to do (i.e. that a thing is hyped does not make it worse than something else - it does not make it better, either, though).
I mean, you're making decisions based on your external perceptions of media stories which is generally not a good way to make decisions. Either for or against something.
ML and AI is used in an absurd number of places both small and large. Most aren't ones that make news stories because they just optimize an existing experience. Sometime too much but that's more of a fault of capitalism and definitely improves the profits of the parent company. Search engines including ones on websites (ie: media, ecommerce, etc.) are powered by ML at any larger company. Recommendations systems are powered by ML and exist on most media and ecommerce sites. Fraud detection of various sorts when it comes to payments and accounts. Even mundane things like internal processes within companies like predicting which columns in a data upload correspond to what.
You aren't entirely wrong. In any hype cycle a lot of money gets thrown at buzzwords, some money "smarter" than others, and a lot of people do things with that money just because money "has to" be spent.
On the cynical flipside though, you can't entirely keep "buzzwords" off your resume simply because recruiters will always squint and "find them" because there's money involved if they do. You are almost always going to get recruiters for whatever the day's buzzword is.
I have a Masters degree and Python experience, and to most AI/ML recruiters that looks like "possible AI/ML researcher". They aren't entirely wrong, I did study AI/ML in grad school. They aren't very right either, because I learned enough to be "dangerous" and came out of grad school a massive AI/ML cynic. (That the field is mostly just Sparkling Statistics and people in general are bad at statistics and easily wowed by Sparkling Statistics. That this isn't the first hype cycle in the field, and it isn't likely to be the last either; we've not really improved on the research of the AI boom in the 1960s/1970s nor the other big AI boom of the late 1980s. They had chat bots then, they had most of the algorithms figured out, including their weaknesses. This boom we've just massively increased Garbage In, Garbage Out to those algorithms and given ourselves enough blinders to pretend that everything is still under control. We haven't solved their weaknesses. We haven't actually made major conceptual leaps. We just have a lot more data and a lot more speed. Which is something the 1960s researchers both predicted and warned us about.)
So yeah, your cynicism here is very valid, at least in my opinion. There's not a lot you can do about it, especially if your aim is to outright avoid recruiters chasing you for whatever VC money is getting thrown at them. I don't have a lot of other advice here other than the only thing you can really do with such cynicism is to apply it as best as you can to improving the things that you have the power to improve.
Ironically, the main project I work on today involves a lot of AI/ML and I'm known as a bit of a wet blanket on the team trying to temper expectations and trying to keep us from doing the worst mistakes ("confidence" values do not mean what people think they mean and showing them in any UI anywhere, especially under the name "confidence" is a massive mistake; machines don't have the "ego" for "confidence", it's a poorly applied statistical term of art that people use to badly anthropomorphize the statistical models). I don't win every battle and I do my best to make it clear I come from a point of pragmatism. It's a hard balance to keep.
I really expected that we'd see a change in my lifetime, that GPs in particular would be replaced by a lower-cost Watson descendant, with there being some other role for patient interaction, wet work, and data entry (perhaps just nurses).
My mom worked for a GP for about 20 years, and it seemed to me that most of what made that guy a doctor was bedside manner + being able to remember a lot of things. But GPs often make astounding amounts of money while leaning heavily on their staff to actually handle patients and keep the business running. I thought it could help drugs get a little cheaper too, because there wouldn't be any point in the pharma companies sending out salespeople to do lunch seminars to convince the GPs to prescribe this or that drug (this still happens).
Maybe this will still happen, but it doesn't seem imminent anymore.
> bedside manner + being able to remember a lot of things
My impression is that accompanying a patient is super important, it helps to understand illness, to have a plan in case of more complex treatments, etc.
Then my doctor has the ability to know me and gauge my health. She's also very good at probabilities and detecting when something really goes wrong.
I'm sure that being able to do that require a lot more than numbers.
(I'm studying data sciences, I trust them, but my guts tell me that diagnosis is in a whole different ballpark)
What many people don't realize is that medicine as a whole is already some sort of expert system (i.e.: a flavor of AI).
There are researchers that conduct experiments to produce meaningful data and extract conclusions from that data. Then there are expert panels that produce guidelines from the results of that research. Most diagnostics and treatments are prescribed following decision diagrams that doctors themselves call... algorithms!
There are several limitations that prevent us from applying other AI techniques to the problem. Off the top of my head:
- We do not have the technology for machines to capture the contextual and communication nuances that doctors pick up on. There can be a world of difference between the exact same statement given by two different patients or even the same patient in two different situations. Likewise, the effect of a doctors' statement can be quite literally the opposite depending on who the patient is and their state of mind. One of the most important aspects of the GP's job is to handle these differences to achieve the best possible outcomes for their patients.
- Society at large is not ready to trust machines to make such intimately relevant decisions. It is not uncommon for patients to hide relevant information from their doctors, and to blatantly ignore the recommendations from them. This would be many times worse if the doctor part wasn't human.
- We cannot apply modern inference techniques (e.g.: deep learning) to the global problem because we have strict rules that prevent medical data collection and analysis without a clear purpose. Furthermore, these techniques tend to produce unexplainable results -which is unacceptable in this field-. As a result, there's not enough political capital to relax those rules.
The attending physician in a modern hospital system is primarily a manager. Their main concern is treatment of the patient's medical issue, but their role isn't limited to that. This patient is refusing care but also refuses to leave, what do we do? How should we schedule care around a patient who requires the entire floor to assist in daily activities of living? They may not get the last word on matters outside of their responsibilities, but being the physician their words carry weight. This role has remained pretty much constant through the modern medical system, even as medicines change and nurses and technicians gain more responsibilities.
A computer cannot perform that role with the current paradigm of AI, even the worst and most arrogant doctor is more qualified leader than any computer.
> We cannot apply modern inference techniques (e.g.: deep learning) to the global problem because we have strict rules that prevent medical data collection and analysis without a clear purpose.
I mean, China will likely do it, as long as they can capture high quality data, so there's that.
“Super important” — more like “super nice-to-have.” Hospitals don’t have any single person on staff who stays attached to particular in-patients. Who knows you? Your chart.
Yes, of course, hospital care would be better in many ways if we did have somebody who statefully understood particular patients’ needs.
But what I’m saying is, the GPs in hospitals could be replaced with stateless diagnostic AI without making hospital care any worse than it is now. And hospital care is a large part of the medical system, so only replacing diagnostics there (while leaving primary-care GPs alone) would still be a major optimization, freeing many doctors to provide better care, go into specialties, etc.
That's simply false. You obviously have no idea how hospital care is actually delivered. To start with, every admitted patient has an assigned attending physician who is responsible for coordinating the care team. Some things can be documented in the patient chart but there are always gaps. Clinical decision support systems for partially automating diagnosis could potentially be helpful in some limited circumstances but the ones built so far mostly don't work very well.
Then where exactly does the oft-cited kafkaesque nightmare of being "lost in the US hospital system" come from (with patients put in the wrong wards and forgotten for sometimes months; given inappropriate medications that doesn't end up recorded; tested repeatedly for the same problems because the test results were "lost"; etc.)?
Just because someone is responsible for you doesn’t mean the system works competently enough to make sure you receive only what you need in a timely manner
> To start with, every admitted patient has an assigned attending physician who is responsible for coordinating the care team.
That's rarely (if ever) a 1:1 ratio. That attending physician is almost certainly juggling multiple patients. Same with the rest of the care team. There's a reason why the first thing one does when approaching a patient bed is to look at the chart.
> Some things can be documented in the patient chart but there are always gaps.
Then those gaps need closed, stat. Once those gaps are closed...
> Clinical decision support systems for partially automating diagnosis could potentially be helpful in some limited circumstances but the ones built so far mostly don't work very well.
...then this will improve considerably. Garbage in, garbage out.
That's largely pointless. The critical data elements do get charted. But time spent closing data entry gaps on patient charts is time not spent actually caring for patients. There are simply not enough clinicians to do all that, or funding to pay them. Furthermore there are many aspects of patient conditions that can't really be coded in a useful way. A skilled, experienced clinician can intuit a great deal from subtle signs like skin color, breathe sounds, tone of voice, small movements, etc. Healthcare relies on tacit knowledge far more than arrogant, ignorant software developers understand.
And in most routine cases the diagnosis is the easy part. The hard stuff is actually working with patients and doing the hands-on procedures, which won't be significantly automated in our lifetimes.
Pattern recognition algorithms do have some promise for computer assisted interpretation of things like medical images and ECG waveforms where the input data is already in digital form. We can't rely exclusively on algorithms for patient care, but if the physician reaches a conclusion different from the human physician, then it's probably worth taking a deeper look and getting a second opinion.
> And in most routine cases the diagnosis is the easy part.
...which is why we shouldn't be wasting such valuable resources (people with an aptitude for medicine) on doing such an easy, routine task all day long, no? It'd be like if chefs spent most of their time hand-grinding spices rather than cooking.
> A skilled, experienced clinician can intuit a great deal from subtle signs like skin color, breathe sounds, tone of voice, small movements, etc. / Pattern recognition algorithms do have some promise for computer assisted interpretation of things like medical images and ECG waveforms where the input data is already in digital form.
You're seemingly contradicting yourself here: you're saying that the places where ML shows the most promise, are exactly with the tasks that would best replace the things doctors are doing. The only reason that ML can't do those things, is that people aren't putting data like "a video exam of the patient by a nurse" into the chart where the diagnostic algorithm can see it / be trained on it.
>Hospitals don’t have any single person on staff who stays attached to particular in-patients.
This is incorrect. Doctors are assigned to patients, and if there is a complication any time or day or night the doctor is contacted to decide what to do. The entire point is so that there is one person who is familiar with the patient, who is also responsible if anything goes wrong. I don't know how malpractice would work with an AI, but given the number of malpractice cases yearly in the US it'd either be sued out of viability or have to be provided with legal immunity(possibly the worst scenario IMO)
Knowing the ontology of your patients and their risk is also a tenet of a doctor's job, but we can do it with AI too. Hell, ontological engineering had a revamp specifically so that we could have a standardized model to describe any and all "parts" of a "whole" in a way that machines could understand.
It also helps to have a relationship with a patient (or person).
There are some people who will never, ever complain about anything. When they complain of severe abdominal pain, for example, you pull out all the stops immediately to figure out what's wrong, because it's probably really bad.
On the other hand, there are hypochondriacs and people will low pain tolerance. While they can certainly also become seriously ill -- and one must never forget this -- the tempo and pace of workup and order of intervention is markedly different, absent other information that shifts the pretest probabilities.
Sometimes a relationship is bad. If you think someone’s a hypochondriac, but in fact they’re unusually sensitive, you’ll dismiss a lot of what they say and that can be quite damaging over time. (Especially if they’re female https://www.health.harvard.edu/blog/women-and-pain-dispariti...).
I wouldn’t eliminate GPs from the process, but many people actually would like to hear what the robots have to say about their medical conditions. Having second opinions of this sort available might lead to better patient outcomes.
There is no evidence that diagnostic robots would actually produce better outcomes. The hypochondriacs are already able to Google their symptoms and make themselves sick with anxiety.
Lol. Maybe people who don’t have any medical problems.
There isn’t enough humanity in healthcare to begin with. Replacement of doctors with AI sounds pretty horrific. General practice isn’t where healthcare costs are going bonkers, and it seems weird to want to cost-cut something that actually kind of works in favor of bullshit.
Know what would be a great use of AI? Something real like analyzing all of the telemetry in EMRs to provide better guidance to doctors to proactively guide people. Some CVSHealth chatbot telling me whatever is a waste of time.
Automated diagnosis applications have existed for decades. They have proven useful in limited circumstances for certain specialties and rare conditions but for routine medical care they're more hassle than they're worth.
That’s me. I really, really appreciate a GP that both understands that I’m not doing it on purpose, and can reassure me that nothing is wrong, or figure out that we actually do need more testing this time.
Unfortunately it’s been years since I had one like that :/
What data is being collected on you? Once a year blood test if that even?
I actually suspect it would be trivial to beat my doctor after 5 years of higher frequency full blood panel data collection.
10 full blood panel samples a year, have 20 million people do that for a data set we can do classification on. I think my doctor is kind of out of business then.
Will never happen in my life though with health insurance and health bureaucracy.
Beat your doctor on what? You can already get 10 full blood panel tests per year if you want. You can just pay for it and don't need insurance. But what will you do with the data? For most people the results won't tell you anything useful.
It won't happen primarily due to government regulation. Medical information has "dangerous, don't touch this" written all over it, and everyone is scared to try.
I used to see this in our country, where 10 people are queueing outside doc's office ( this is public health system) when some well dressed man goes straight into the office not even bothering to ask if there's anyone in there and fast forward a few min and the doctor is 'on break', whilst drinking coffee with the sales rep, while all those people sit and wait. Eventually it got outlawed.
That's extremely rude. How could he just barge into the doctor's office? A physical examination could be taking place.
In my experience at a specialized neurology practice: they wait outside until the doctor is free, then knock on the door and ask if they have a moment. They would almost always get straight to business, never wasted more than half a minute of people's time socializing.
Drug companies offer a lot of free samples. It's the same drugs the psychiatrists were going to prescribe anyway, they're just trying to get them to prefer one brand over the other. Sertraline, for example, is first line treatment for depression, anxiety. Getting free sertraline samples reduces costs for patients and really helps them out. Especially in my country where generic medication is often found to not be of the same quality as those manufactured by big pharmaceutical companies.
Everyone talks about the relationship between drug reps and doctors like it's the most incestuous, evil, corrupt thing. How else are doctors, especially those who are 10, 20 years removed from their residency, supposed to learn about new treatments and medicines? Alexa, what is best current treatment for a duodenal ulcer? You think a doctor is going to spend his limited downtime perusing the PDR (which no longer exists, and was always heavily influenced by the drug manufacturers anyway)?
Sure, there may be some excesses (although the truly major perks like entire vacations dressed up as a "conference" no longer exist), but I would much rather have doctors be aware of new drugs and yes, subject to marketing pitches, than have these drugs languish (eventually leading to drugs not being created) because nobody knows about them.
Part of the job, as stipulated by medical regulators around the world, is keeping up-to-date with evidence. This can be achieved by reading journals and attending conferences, in theory.
But.... journal publishers exploit their monopolies, and conferences are funded by corporate sponsors. So perhaps they're not so different.
Medical conferences basically would not exist if it wasn't for suppliers and drug companies paying for sponsorships, trade show booths, opportunities to speak, etc. Not really any different than any industry's trade conferences.
Sounds just like every technology conference I've ever been to. A bunch of software and hardware vendor booths, and most of the speakers being authors hawking their latest books.
It's their responsibility to stay up-to-date. If a dev can keep up with front end tech stacks, doctors, who are much more elite in their education, should keep track of latest treatment breakthroughs in their domain of expertise.
First of all, the vast majority of devs do NOT stay "up to date." Most know one language or even just one platform... i.e. "WordPress developer" or "Oracle admin". Secondly, how do you think YOU hear about new technologies... usually due to marketing. Did React just come out of nowhere? No, Facebook marketed it relentlessly. Did people discover Kotlin on their own? No, JetBrains and Google hit people over the head with it. Etc, etc
Is it really the case that Facebook marketed heavily React? Why? What do they gain from it? Real question, or not like react was an entry point to their API?
It was fairly obvious when it was an up and coming thing. They sent out engineers to talk about it, you had these articles popping up about it more or less out of nowhere, etc. If you weren't there (which I'm guessing you're not, otherwise why would you ask), it is hard to imagine. Perhaps it makes more sense when you consider how normal "advertorials" are now.
Take a look at what that actually entails. Inexpensive online courses with guaranteed passing exams, many of which have zero to do with actually treating sick people -- Secondhand Smoke. Medical Ethics. Herbal Medicine Review.
Even if a practitioner took it seriously and wanted to get a real education about actual medical issues, they aren't going to find coverage of brand new drugs in an educational setting unless it was arranged by the drug companies themselves.
> How else are doctors, especially those who are 10, 20 years removed from their residency, supposed to learn about new treatments and medicines?
With some other mechanism that doesn't have major conflicts of interest? Like, I don't know, attending to actual courses, like any other profession that requires continuing training.
Who is teaching the courses? Where do they get their info? Given the very limited oversight of "continuing education", it's trivial for Merck or Pfizer to ensure their advocate teaches the class or records the online seminar -- with zero requirement that they disclose that fact. At least when a drug rep visits the office and buys lunch, you know the source.
In Illinois Doctors have to go to a one week conference every year that is supposed to talk about this stuff. They also have to take board exams every few years that make sure they're staying caught up on new advances.
It's 60 hours every 3 years, of which webinars are acceptable, and no records need to be submitted with the renewal application. There are no tests or exams. The "new advances" they must keep up on include Sexual Harassment Prevention and Implicit Bias.
Study what? Even the New England Journal of Medicine is full of articles funded by drug companies. And for good reason -- the results of drug trials should be communicated to physicians. Buying them lunch may be less prestigious, but it's essentially the same thing.
There's more material available, not just scientific journal articles. The medical specialty associations periodically release detailed guidelines covering new criteria, methods, treatments. For example:
There are courses available if you wish to be taught. There are events where people present new developments. There are paid sites like UpToDate. Even textbooks eventually get new editions and there's always plenty of fundamental science in them that doesn't change
Did you check the Disclosures section of your article? Are there any drug companies NOT included there? Like it or not, private companies fund the vast majority of medical research in the U.S., and any doctor who wants to stay up to date cannot (and should not) ignore it all.
The authors have no conflict of interest to declare, but declare lecture honoraria or consulting fees as follows: T.U., Bayer, Boehringer Ingelheim, Hexal, Vifor Pharma; C.B., Servier, Menarini, Merck Pharma, Novartis, Egis, Daichy Sankyo, Gilead; N.R.P., Servier, Pfizer, Sanofi, Eva Pharma; D.P., Torrent Pharmaceuticals; M.S., Medtronic, Abbott, Novartis, Servier, Pfizer, Boehringer-Ingelheim; G.S.S., AstraZeneca, Menarini, Pfizer, Servier; B.W., Vascular Dynamics USA, Inc, Relypsa, Inc, USA; Daiichi Sankyo, Pfizer, Servier, Novartis, Menarini, Omron; A.E.S., Omron, Novartis, Takeda, Servier, Abbott.
The NIH funds a huge fraction vast of biomedical research in the US. Pharma does important work too, but it’s largely concentrated in the very last stages of getting a product to market.
These COI disclosures also strike me as hard to interpret. It’s certainly possible that some of these people are deeply invested in a company and are pushing its particular therapy hard to buy a new boat or something. However, I’d bet many of them are $250 to participate in a focus group, or free conference registration to be in a panel. It’s important to know who’s buttering the authors’ bread, but it’d be helpful to know how much it’s being buttered too.
> The NIH funds a huge fraction vast of biomedical research in the US.
This document https://www.researchamerica.org/sites/default/files/Policy_A... states that in 2017 private industry spent $121 billion on Medical & Health R&D Expenditures in 2017 compared to $39 for the federal govt ($32 of which is NIH). $121 billion in a single year -- I honestly assumed the number was in millions till I re-read it.
You are probably right that the drug companies are (not surprisingly) focused specifically on drugs while NIH research is more general and widespread. But that is still a very large difference.
I did see that. I don't see that as a reason to doubt the recommendations of this particular article.
I thought we were talking about direct marketing by pharmaceutical company representatives by the way. It is of course impossible to separate modern medicine from the pharmaceutical industry since many therapies depend directly on them. It's still the doctor's job to figure out which medicines are actually good and what's merely some salesman's product.
> I don't see that as a reason to doubt the recommendations of this particular article.
No conflict of interest, except they're directly paid by drug companies. That's the sort of thing you'd expect to see in a banana republic, not established medicine. It should call the integrity of the entire system into question, frankly.
Why is "direct marketing" (drug reps) verboten but an article paid for by the same company is legitimate? What if the reason for the drug rep's visit is to bring a copy of the article to the doctor?
> Why is "direct marketing" (drug reps) verboten but an article paid for by the same company is legitimate?
Scientific articles are published and read by the community. There are, for example, social media and messaging groups where doctors will post and discuss articles, including their methododology and limitations. There's always the possibility that the study could actually be relevant.
Drug company representatitives talk to doctors in private in order to try and convince them to prescribe drugs. Like all marketing, there's an inherent dishonesty to it. You always assume they're overstating the positives, downplaying the negatives and ignoring alternatives. Doing this is actually the doctor's job. It's our job to pick these claims apart and figure out what's true and what isn't so that patients don't have to do it.
Doctor-drug industry relationship is at its healthiest when they're just giving doctors free samples of the drugs they were already going to prescribe anyway. Doesn't change the doctor's conduct and helps patients with free medicine. Doctors are already going to prescribe angiotensin receptor blockers for hypertension, drug company representatives won't change that. They can and should provide free samples though, free medication helps everyone.
> Drug company representatitives talk to doctors in private in order to try and convince them to prescribe drugs.
Everything a drug company does is ultimately about selling more drugs. It's not limited to the drug reps.
> they're overstating the positives, downplaying the negatives and ignoring alternatives
Again, not at all exclusive to drug reps. This behavior can be traced all the way back to Phase I of the clinical trial.
Your position in this thread makes no sense. I stated the drug reps help doctors stay up to date on the latest drugs and treatments, you disagreed and said doctors should "study. continuously." What should they study? Articles sponsored by the drug companies. How can you square that? Further, I'm sure you're aware that only a tiny percentage of doctors actually read the fancy journals and fewer understand the statistics and the details (perhaps those are the docs who sit around on the message boards you mention). For the other 90+%, the drug reps are the conduit who deliver relevant info to doctors. Ate they aggressive? Yes. Sneaky? Sometimes. Ultimately, do they help doctors discover drugs that help their patients? Unless you believe the drugs being approved by the FDA are ineffective, the answer is yes.
>that GPs in particular would be replaced by a lower-cost Watson descendant
It is happening. They are called physician assistants and nurse practitioners, "supervised" by a doctor. I assume going forward, they will take more and more of the usual pink eye/ear infection/flu and other common work that does not require 6 to 8 years of post bachelor education.
Yep. The midlevels are supported by automatic protocols in Epic (e.g. sepsis, DKA -> put these dozens of orders in with 5 clicks) that physicians decide on and approve. They also rely more heavily on imaging instead of a physical exam and history. When unsure, they can consult a physician, even a specialist.
It’s a very polarizing topic in medicine that patients generally aren’t privy to. Especially for resident physicians who often make half as much as these midlevels yet have more education, there’s a lot of bitterness. The federal government is ultimately to blame… having a fixed number of residency spots to artificially limit the supply of new physicians is terrible, and this is the predictable result.
I think hospitals support inefficient midlevels because they can bill patients for the increased resource usage, but it’s not good for the system overall when unnecessary scans and consults are done, and more complex patients don’t get comprehensive care. Many foresee a two-tiered system developing, where the rich see physicians, and the poor see midlevels.
>Many foresee a two-tiered system developing, where the rich see physicians, and the poor see midlevels.
There already was a tiered system, with rich people being able to buy concierge medicine and getting preferred treatment based on who knows who on the hospital's board or if their name is on a wing of the hospital.
The change now is a more visible and more granular price segmentation.
There’s no price segmentation. You pay the same for a visit with a PA or NP as for one with a physician, so why see someone with less than a tenth the experience who may have gone to an online only school with 100% acceptance rate and shadowed for 500hrs of “clinical experience“ right out of nursing school?
It will happen via in network and out of network agreements.
Healthcare providers with greater proportion of NP/PA will be selling for cheaper, so MCO will sell access to only them in their lower price plans, and healthcare providers where you get to see doctors will be in higher price plans.
This already happens, especially with many healthcare providers not accepting lower reimbursed Medicaid patients.
A two tiered system might actually be better for improving access to affordable health. Mid-level providers seem to achieve equivalent outcomes for routine cases at lower cost.
I agree that Congress should increase funding for residency programs.
I generally dismiss these “equivalent outcome” studies. Any midlevel will (and should) bounce the more complicated cases to their supervising physicians. Outcomes at that point are meaningless.
There’s definitely a trade off between resources devoted to education vs. acceptable risks from failed procedures, missed/delayed diagnoses, and increased utilization of imaging and referrals (and the physician radiologists and others who participate in that - it goes full circle). Physicians now are probably on one extreme end of that, and midlevels on the other.
On the topic of servicing rural areas… the problem is that nobody with better options (which includes midlevels) wants to live in these places. These educated, high-earning people want to live in urban areas, and they can. CMS has tried to incentivize this with billing by offering higher reimbursement rates to rural places that have a midlevel on staff. That’s about it, though.
> I generally dismiss these “equivalent outcome” studies. Any midlevel will (and should) bounce the more complicated cases to their supervising physicians. Outcomes at that point are meaningless.
If midlevels can successfully detect complicated cases to a supervising physician, and handle a whole lot of other care independently... and the net result is equivalent outcomes... this isn't a massive win? You've conserved the really expensive and contended resource for where it's needed and not made anything worse...
#1 - Funky/misleading statistics - Generally they claim that these NPs with uncomplicated patients do as well as physicians with complicated patients. It's not claiming that of any randomly selected patient, regardless of who they see, the outcome is the same. Therefore, if uncomplicated patients saw physicians, outcomes for the physicians could improve. In primary care managing hypertension or diabetes, this isn't as pertinent. For something like anesthesiology, it's more so counting how many times shit hits the fan, and brain cells die when the anesthesiologist takes time to be summoned.
#2 - They're not conserving expensive resources. Imagine a patient comes in with a lump on their hand. An NP might see a weird lump, order an MRI which gets read by a radiologist, refer to an orthopedic surgeon who specializes in the hand, who removes tissue to send to a pathologist, who determines it's a common benign tumor of the fascia. That's three physicians who spent much more time here! The patient no longer has use of their interphalangeal joints. The physician would probably try to shine a light through it, note the patient's Scandinavian ancestry and family history of plantar fasciitis, and tell them to live with it and come back if it changes.
No resources were saved here, but the patient's DASH score (disability of the arm, shoulder, and hand) is still 0 so the outcomes are the same.
This happens all the time.
#3 - Bad incentives - Medicaid would not in a million years cover this, but the game of medical pinball where patients bounce around through in-network referrals can funnel those with decent insurance into procedures. Especially when most people have poor health literacy. A hospital executive probably just splooged in his pants seeing how much money their loss-leader of primary care is driving to radiology and the surgical specialties where they actually make money.
#4 - It's insincere. All of this can be viewed as possibly successful when the midlevels are part of the healthcare _team_ and know their limitations. But the NP groups are increasingly pushing for independent practice and prescribing rights in state legislatures across the country. CRNAs require a physician supervisor... in many places, that doesn't necessarily need to be an anesthesiologist, and the surgeon performing the procedure can suffice. The AANA recently changed its name to the "American Association of Nurse Anesthesiology"... It used to be "Anesthetists". The CEO and president (two different people) of the American Nurses Association both refer to themselves as "Doctor" in a healthcare setting even though one holds a DNP and the other a PhD. It's pervasive.
> Generally they claim that these NPs with uncomplicated patients do as well as physicians with complicated patients.
The studies I've seen have compared practices where NPs are seen first vs. physicians are seen first.
> They're not conserving expensive resources. Imagine a patient comes in with a lump on their hand. An NP might see a weird lump, order an MRI which gets read by a radiologist, refer to an orthopedic surgeon who specializes in the hand, who removes tissue to send to a pathologist, who determines it's a common benign tumor of the fascia. That's three physicians who spent much more time here!
Your claim is this kind of excessive testing and referral doesn't happen with physicians? Do you have some kind of evidence this is more common with NPs?
This kind of overtesting leading to unnecessary procedures and bad outcomes has been pervasive through care in the US. Don't blame it on NPs.
> Bad incentives - Medicaid would not in a million years cover this, but the game of medical pinball where patients bounce around through in-network referrals can funnel those with decent insurance into procedures. Especially when most people have poor health literacy. A hospital executive probably just splooged in his pants seeing how much money their loss-leader of primary care is driving to radiology and the surgical specialties where they actually make money.
Ditto
> It's insincere. All of this can be viewed as possibly successful when the midlevels are part of the healthcare _team_ and know their limitations. But the NP groups are increasingly pushing for independent practice and prescribing rights in state legislatures across the country. CRNAs require a physician supervisor...
Welp, we're not creating anywhere near enough residencies to create enough physicians to do the work, so I'd suggest we'd figure out ways to either do that or use people with lower levels of training well (preferably both!).
I'm having a hard time understanding why they would be bitter. Residency is temporary and a part of the training process. Once completed, doctors will make 2x-3x+ compared to midlevels for the rest of their careers.
Residency has a lot of problems. The match is stressful enough. Medical school graduates carry a huge amount of debt, but must complete residency before earning enough to meaningfully pay it off. Residencies pay 40-85k and most resident physicians are expected to work 80+ hours per week. 80 is the theoretical maximum, but that doesn’t count time arranging work, studying, taking board exams, etc.
All this, and if you don’t complete your residency, you have no prosperous future as a doctor. You might re-match to another residency if you’re very lucky. The hospitals know this and act accordingly. Residents and even medical students paying tuition (!) were assigned to treat COVID patients and couldn’t really decline without risking the future they’re heavily invested in.
Keep in mind, the federal government pays ~150k per year to the hospital for having the resident. Yet the residents are often more indentured workhorses than trainees. It’s not uncommon for entire departments to run overnight with only residents, but no attending physicians.
Now imagine being in this situation, and not being allowed into the “providers lounge” because you’re a resident. Or using a broad-spectrum antibiotic instead of something more specific and being scolded for poor antibiotic stewardship, while the NP who has “completed their training” can’t even properly decide antibiotics are indicated some of the time. And if that NP were ever treated the way a resident is, they could go get a job at the hospital on the other side of town and start in a week.
Because the future is for doctors to not make 3x compared to them. The mid levels are being used to increase supply of healthcare, using the doctor’s license for liability, in order to reduce the price doctors collect (per unit of time and effort).
Basically, they are watching their expected wealth / purchasing power be reduced.
If someone was making more than twice as much as you, working half as many hours as you, seeing half as many patients as you, and were less qualified for their similar role, you would be upset too.
It's happening because hospital corporations love them.
Corps can pay less, and since they have a tenth of the education, they order tons of profitable tests, consults, and scans because they don't know otherwise.
This is why insurances are moving toward capitated plans. Instead of paying for services provided health care providers get paid per patient they care for. That way the perverse incentive created by asymmetric information is removed.
Well implemented capitated plans are value based. Value based just means there are incentives for better than expected health outcomes and disincentives for bad outcomes. If you have a non-value based capitated plan health care providers would reduce the quality of care, so value based strategies were implemented to ensure patients receive good care even though providing it costs money.
It's a mischaracterization for PAs because doctors only have ~7.5x minimum more clinical training and not 10x, 15000 clinical hours (for med school + family medicine, the shortest residency program) vs 2000hrs. Ask any radiologist you know what they think about the imaging orders from NPs and PAs and that will give you your answer.
>Corps can pay less, and since they have a tenth of the education, they order tons of profitable tests, consults, and scans because they don't know otherwise.
Hence the purpose of managed care organizations (MCOs, health insurance companies) employing people to approve and deny (or design systems that approve or deny) payment for unnecessary tests, consults, and scans. And in a taxpayer funded system, the government employs people to performs the same roles.
It's worth noting that the higher tiers of nurses have at least a masters degree, and like more time working than a doctor spends in residency. They are highly trained/skilled professionals.
I would guess that most people entering NP programs at this point have less than 3 years of work experience as a nurse, a job where you are not diagnosing, coming up with treatment plans, performing procedures or doing any other physician tasks.
I don't know if 500hrs of shadowing after a 2yr part-time online only program that you don't need any nursing degree or experience to enter would count as highly trained or skilled. Here's a list of direct entry nursing masters programs - https://nursinglicensemap.com/nursing-degrees/masters-in-nur...
Here's Johns Hopkins doctor of nursing practice program's curriculum - https://nursing.jhu.edu/academics/programs/doctoral/msn-dnp/... - where more than half of your classes are not medicine related and which requires an astounding 1000 clinical hours and less than 10 credits a semester before you can call yourself "doctor". Most medical students will have 1000hrs after 3 months in 3rd year, where they will be expected to diagnose and come up with treatment plans vs just shadowing, and they still have 9 more months of 3rd year, 4th year, and a minimum of 3 more years in residency. Doctors will likely end up with a minimum of 15000 hours of training. The difference really is that large, and I feel bad for the patients and for the NPs who have no idea how deficient their education is. PAs have 2000hrs of clinical experience. Here's a chart - https://i.imgur.com/Cj5z4f8.jpg
I didn't say that nurses have the same medical training as a doctor of medicine; just that they are highly trained professionals with a fair amount of experience. If you match the 3 years of residency with 3 years of working as a nurse (they're clearly not the same thing, but both are "experience" for the purposes of this discussion), a starting medical doctor has 2.5-3 more years of training/school/experience than a nurse practitioner. That's a lot; but it doesn't reduce the fact that the NP has a lot of training. The post I was replying too sounded like it was dismissing the amount of training/experience being a NP takes, and it bothered me.
the real problem with NP/PA is now what they know. It is that they don't even know what they don't know. There's a large body of basic science, biology, that a doctor has to acquire that helps underpins a lot of the clinical medicine they practise. It's not just following guidelines and algorithms. It is understanding why the guidelines are, it is understanding why what looks like a typical case isn't, but is that one rare thing you absolutely can't miss.
Honestly, if not for the weirdness of the US system, mid-level providers shouldn't exist. But we are where we are. There absolutely is no room for independent practise for mid-level providers.
Is there any evidence that patients of NPs actually have worse outcomes? Given the current physician shortage would it be better to wait to see one, or get an appointment with a NP right away?
My expectation is that the outcomes would be similar for the common issues, and would start to deviate as you got into more uncommon problems. A doctor will have a lot more "background knowledge" to be able to consider things that are outside the every day. At least in my mind, it's not unlike someone in software development with a degree in it vs not. For most things, the person without a degree will do a fine job; but for some things, they won't be able to consider many of the possible options/tools, because they just haven't been exposed to them.
correct. except the person doesn't even know when they don't know. and that's the most dangerous part. If you at least know what you don't know, you can re-direct to the right resources.
Many studies comparing NP and physician outcomes will have the NPs under supervision by physicians, which is ideally how they would be used, but in practice the true supervision level varies widely. I wouldn't see an NP for my care personally, and I doubt there are many physicians who would. The wait time to see primary care physicians is typically less than a week in most places and would be worth it. If you're experiencing something you feel is too serious to wait a week I would visit the ER (and make sure to ask to be seen by the physician also). It's your health. Personally I would only trust mine to the people who are the experts in their subjects, and not those who have less training and can switch between specialties without any additional training.
I don't have anything against NPs when the supervision is close, but more and more doctors are put into positions where they are acting as liability sponges for de-facto independent NPs/PAs.
Here are a few studies -
(CRNA) We found an increased risk of adverse disposition in cases where the anesthesia provider was a nonanesthesiology professional. https://www.ncbi.nlm.nih.gov/pubmed/22305625
NPs/PAs practicing in states with independent prescription authority were > 20 times more likely to overprescribe opioids than NPs/PAs in prescription-restricted states. https://pubmed.ncbi.nlm.nih.gov/32333312/
Both 30-day mortality rate and mortality rate after complications (failure-to-rescue) were lower when anesthesiologists directed anesthesia care. https://pubmed.ncbi.nlm.nih.gov/10861159/
Compared with dermatologists, PAs performed more skin biopsies per case of skin cancer diagnosed and diagnosed fewer melanomas in situ, suggesting that the diagnostic accuracy of PAs may be lower than that of dermatologists. https://www.ncbi.nlm.nih.gov/pubmed/29710082
Nonphysician clinicians were more likely to prescribe antibiotics than practicing physicians in outpatient settings, and resident physicians were less likely to prescribe antibiotics. https://www.ncbi.nlm.nih.gov/pubmed/15922696
The quality of referrals to an academic medical center was higher for physicians than for NPs and PAs regarding the clarity of the referral question, understanding of pathophysiology, and adequate prereferral evaluation and documentation. https://www.mayoclinicproceedings.org/article/S0025-6196(13)...
I will add my anecdotal perspective as a rheumatologist at a tertiary care centre to your second last reference. I have a lot of respect for the work my NP/PA colleagues do, particularly on the ward. Yet I see a notable difference in the quality of referrals from MDs vs. most NPs/PAs whether it be from clinic, ER, or ward. With some exception it's often please see for [subjective complaint], a + random test that was checked, and query [disease that goes with that antibody] or a misunderstanding of what I see in my discipline. Not to say that MDs have it perfect but I'm not sure if it's the shorter training, more algorithmic focus, less confidence in their physical exam that drives this. As a healthy 20 year old I'd have said an NP/PA is great for primary care but I just don't see it as a solution as people age and get more medically complicated.
In my country, patients will go to the public healthcare unit at 4 AM in the morning in order to try and get an appointment. It opens at 8 AM and by that time there'll be a queue of about 30 people. Doctors are expected to see them all before 11 AM. Such is life in "family medicine", theoretically a medical specialty but mostly filled with doctors who just graduated medical school and who are looking to make some money before they start residency which pays a pitiful "scholarship" and is essentially indentured servitude anyway. There's barely any time to do anything more complex than chief complaint or chronic disease management.
It's funny because it's the complete opposite of what family medicine was supposed to be. The doctors were supposed to live and work in those towns so they could get to know the population and form stronger bonds with the community. Instead, they either burn out quickly or move on to far better working environments, specialization or not. Some of these public healthcare units don't even have sinks you can use to wash your hands.
This is more or less the case in many European countries. Less so here in the UK, but approaching there rather quickly due to astoundingly poor management by various successive governments. It’s tough back in South Africa as well, and they pay their doctors extraordinarily well.
This is true in the US, too. GPs have become "procedure mills". It's almost as if management figured out they just have to put the right code on the bill enough times a day. Since no one is accountable for outcomes, money happens.
I've heard Canada is like that. I've had similar experience in South Africa, even in private health care, but I definitely had the impression that my doctor somewhat cared about me, especially after going to them for a few years
It is so in China and it is every 5 minutes in most cases.
Precisely because of this, I chose doctors from good public hospitals because of their super rich experiences instead of fancy private hospitals.
Yeah like most businesses the owner his staff to help out. I’m curious what you think GPs actually make, because in the US it’s not astronomical. Watson went after the wrong problem— doctors don’t comprise huge amounts of healthcare spending. It’s a recurring issue, tech thinks they have a solution and in reality the devs don’t have a good grasp on the actual landscape they’re playing in.
There is no need to market to Doctors now when they market directly to consumers who go demand they get the new medicine.
If we want to reduce costs, we need to move to lower level providers like a LPN or CRNP. Most people coming into a GP have the flu or an ear infection or .... and that can be handled by them. There will be one MD and to handle complicated cases and to supervise. We've already switched so that intake is done by CNA making $15/hour. In the US at least working at FAANG pays far more than being a GP.
According to the Bureau of Labor Statistics, the mean salary of "family and general practitioners" in May 2020 was $214,370 [1]. This figure includes salaries from GPs throughout the country (i.e., not just in the Bay Area).
You can also look at median salaries. According to the BLS, all ten of the occupations with the highest median incomes in the U.S. are medical occupations [2]. "Family medicine physicians" are 10th on this list.
Mediocre GP makes 200k cash in Omaha or any average city and has choice among many employers and systems. Stanford CS represents top talent and moreover does not make 200k cash in Omaha, and can only make the big bucks at a fixed number of entities in fixed locations with fixed hierarchies and systems.
A freelance GP (waarnemend huisarts) in the Netherlands makes on average 65 euros per hour... It pays better to be a freelance software engineer. Less education required, less responsibilities, impact of mistakes is also usually less.
USA has an extremely inefficient system of training for doctors which wastes literally years of human potential. First you go to university from 18-22 but not even 2/3rds of the year. The rest of the year is some level of waste for most students. You often purposefully dumb down and study less rigorous subjects than an engineer because you need all top grades to be get into medical school and can't risk it. Then medical school is an excessively long four years which has further periods of time waste and a lack of integral training until late in the process. Then there is a highly unfocused three year residency with what are widely understood as illegal discriminatory labor requirements holding on to their anachronistic 1910 white-male origins by a proverbial thread. So at age 29 you can finally be a GP after many unnecessary years of wasteful, repetitive, unfocused study, vacations and debt. This exclusivity and opportunity hoarding results in a reasonably high skill at a very very unnecessary level of cost and personnel shortages.
Dutch system is quite similar: 3 years bachelor, 3 years masters, including 18 months coschappen (residency), and then 3 years of specialization to GP (other specializations take longer). (https://universitaire.bachelors.nl/faq/ik-wil-dokter-worden/)
Many specializations come with very low job opportunities, being a GP is very stressfull: low paid assembly line type of work, a GP is expected to see 6 patient per hour, do home visits, follow up with patients and hospitals, and run a practice, manage employees, follow lots of trainings, etc. Having your own practice as a GP is not very popular any more, a lot of GP just want to freelance part time, not having the additional stress of running a practice.
Reimbursement for GP services in the USA runs $150-$300/hour depending on whether you are seeing elderly patients or people on employment plans, and a doctor will see about half that, plus or minus depending on the setup. Hence $200k per year if a doctor sees about 6 or 7 hours of patients plus a few hours of paperwork, calls, and emails 5 days a week.
Those are both people problems. Tech can't solve many people problems, especially something as entrenched as healthcare. Isn't it huge, something like 10% of the US economy?
Why do you think nobody important (politicians, primarily) is really trying to solve those major healthcare problems?
If politicians are willing to pork and barrel over a random soy farm employing 2000 people, for sure they're not going to throw away, say, 5% of the US GDP and possibly 5% of all employment in the US.
I don't know how you're going to get out of it...
[1] "There were 22 million workers in the health care industry, one of the largest and fastest-growing sectors in the United States that accounts for 14% of all U.S. workers, according to the Census Bureau’s 2019 American Community Survey (ACS)."
To put it even further into perspective, that's 2x as much as comparable western nations with single-payer, who have similar or better outcomes in most cases.
We have this health system to avoid taxes, but this crazy US system probably costs 97-98% of Americans pay more for health stuff than all of their actual taxes combined.
It's funny how on these forums people who actually do something good and useful like GPs are considered overpriced, but at the same time many here work for FANGs or other webad businesses often making more than GPs. I know that if it comes to decide between the health industry and Facebook, Google, Apple or MS I sure know which I'd rather keep.
Interestingly, I assumed they were outside the US. Primary care docs (especially independent primary care docs) are one of the lowest paid medical doctors. Most specialists make significantly more money (and have a significantly better workload/schedule).
> My mom worked for a GP for about 20 years, and it seemed to me that most of what made that guy a doctor was bedside manner + being able to remember a lot of things.
That’s exactly right, but there’s nothing wrong with that.
A good doctor’s memory of patients spanning decades of a career and all of the various treatments that they did or did not respond to is very valuable. It’s a good thing that they offload as much as possible to other people so they can focus on doing what they do best.
I think the comment above, most charitably read, is that a lot more people would have access to high-quality healthcare if you could put this work on robots instead of people, because computers excel at storing data and looking it up accurately and following predetermined rules. There would be fewer cases of people going to their doctor and being told "oh, it's nothing" when it actually is a specific, rare, and urgent problem. And then they would end up going to a human specialist to figure out how to fix that problem.
> most of what made that guy a doctor was bedside manner + being able to remember a lot of things.
Sure, that, and recognizing patterns and adjusting medication and being able to use good judgement for when to escalate to a referral for a specialist. But that's a lot!
I actually go to a teaching hospital for my primary care. It means I get seen by residents, and almost always also by very experienced teaching doctors. It ends up meaning that I get more time and attention by people who are actively learning and trying hard to do the right thing. The trade-off is there's no long-term trust relationship, but I am OK with that. I've also experienced care from elderly family doctors who run a "one-man-band" with a nurse and a receptionist, they're nice but I think I get better care at a teaching hospital.
> there wouldn't be any point in the pharma companies sending out salespeople to do lunch seminars to convince the GPs to prescribe this or that drug
Right, but there would be a lot of point in making deals with whoever builds Watson-like devices, to turn them ever-so-slightly more likely to prescribe one drug over another or make one diagnosis over another. It might even be cheaper than hiring and sending out a bunch of salespeople.
> GPs often make astounding amounts of money while leaning heavily on their staff to actually handle patients and keep the business running
I’ve seen this in Japan (ish), but in the Netherlands it’s definitely the GP’s doing most of the job. The assistant just does bookings and waves me in when it’s my turn.
I thought the same, but as I grow older, I believe people would reject this. Even a subpar human GP would be much more accepted than a computer. That's not necessarily true in some societies though, e.g. Japan probably would accept it.
That said, I would probably focus on fixing the system first in a way that a significant percent of population doesn't need to order fish medicine off amazon to get treatment.
I wouldn't mind seeing a computer first before a GP. A lot of the time a GP will say something like "here try these tablets and come back in a week". The true worth of a GP is the follow-up appointments and understanding conditions over time.
> I really expected that we'd see a change in my lifetime, that GPs in particular would be replaced by a lower-cost Watson descendant, with there being some other role for patient interaction, wet work, and data entry (perhaps just nurses).
Perhaps this indicates a major gap in your visibility into and understanding of modern medical practice?
> My mom worked for a GP for about 20 years, and it seemed to me that most of what made that guy a doctor was bedside manner + being able to remember a lot of things.
"being able to remember a lot of things" -- Yes, absolutely. This is an area where AI-assisted decision support (like Watson) could be, and I hope will be, extremely valuable.
OTOH, you also rightly recognize bedside manner -- as anyone who has been a patient or a patient's family caregiver will attest, this is an essential component of core, and I think likely also the healing process. We won't get this from a machine until there is a true general purpose AI, at which point I expect an AI singularity anyway.
But consider that there are other factors of the practice of general medicine that you haven't even touched upon. For example, liability: In the office you envision, where Watson/AI makes medical decisions and these are executed by other roles like nursing, where does ultimate responsibility (and legal liability) lie? Remember that Watson outputs probabilities -- suppose the following:
Chance of disease X: 89%
Chance of disease Y: 10%
Chance of disease Z: 1%
If disease X, intervention A has an 80% probability of success.
However, if disease Y, intervention A has an 80% probability of harm.
(before you object that this is contrived, this represents a realistic situation I encountered recently, where intervention A is high dose steroids)
Now, will we put the onus on the patient to select an intervention? I don't think that would be very popular. While I certainly do not advocate paternalism, when faced with difficult decisions quite many people openly defer to their physician.
> But GPs often make astounding amounts of money
I suppose this could be true for some definitions of "astounding," but it's generally accepted that GP/"primary care physician" pay is essentially the lowest of all specialties , which is a major contributor to lack of access to primary care in industrialized countries (while you'll not have a hard time finding a private pay dermatologist, for instance)
ANd on top of this, we are posting on HN where a mid level software engineer total comp can EASILY outpace the average US primary care physician salary.
> while leaning heavily on their staff to actually handle patients and keep the business running.
Do not all professionals and business executives rely on highly trained staff as force multipliers? This is a fundamental principle of the advancement of human economies. It is grossly inefficient to operate with individuals as "jack of all trades" when they can instead each become specialized to support a bigger or broader goal.
By "leaning heavily on their staff to actually handle patients and keep the business running" are you suggesting that the primary care physician should be performing check-in, insurance verification, rooming, vitals measurement, blood draw, medication administration etc? That is a certain recipe for massively decreased throughput and shortages/decreased access to primary care.
> I thought it could help drugs get a little cheaper too, because there wouldn't be any point in the pharma companies sending out salespeople to do lunch seminars to convince the GPs to prescribe this or that drug (this still happens).
This has been massively curtailed for 20+ years, at least in the US. I am not sure about other countries. But overall I think this is a seriously minor portion of the (exorbitant) price of medications in industrialized countries.
In any case, I doubt it would make much of an impact on utilization in most contexts, as insurance/health plans/prescription benefits have already implemented fairly strict guidelines-based formularies and coverage tiers (again, at least in the US -- I can't speak to other industrialized countries, although I expect they are similar or even more strict)
(edit: another poster points out all the direct to consumder drug advertising -- I agree - this probably has a much bigger influence in 2022; ad budgets are absolutely insance)
> Maybe this will still happen, but it doesn't seem imminent anymore.
Here we agree. I am certain we'll see AI-assisted physician decision support, but (a) the physician won't go away and (b) I think it'll be an unfortunately long ways in the future.
> ...I won't even use the self-service kiosk at McDonald's
As lame as it may be, but I just used the McDo kiosk for the first time.
Why? I'm a very infrequent customer at McDo and have 0 knowledge of options and combos, but also remember the mutual annoyance when previously asking for menu details from a min-wage clerk.
In a perverse way, the kiosk gives that power to choose back to me, the customer. At the same time relegating the supposedly more able humans to even less meaningful role.
This worked quite right in this case. I can see this approach applicable as well for some medical need that could be mapped onto a sequence of a "few" choices.
This could be resulting in some assistive pre-screening report.
Well, that's the stuff the assistants do at the beginning of a doctor visit. Not that different from a slot-operated scales of ancient times.
But in the end, I still want to see an immediate human responsibility in such transaction. By the same token, a GP won't be leaning heavily on such "assistive report" and would still go on and ask all of the questions again, as trained, as allotted, as billed.
Each doctor visit begins as a custom solution, no matter how cookie-cutter it turns out to be at the end. That's what we expect and that's what it ends up being billed to us.
Medicine is a business. Its incentive is profit, not patient outcome. Everybody knows the problems with medicine and the solutions are straightforward. But they don't result in more profits, only better patient outcomes. So you only get advances when it increases profit.
Come up with a way for better patient outcomes to result in higher profits and you'll see advances in patient care real damn fast.
1. Stop charging so much. People aren't seeking treatment because they're afraid of the bills.
I have other solutions, but there's no point in listing them because nobody will implement them (for the same reason that one won't be: profits over patients)
Of course AI could replace doctors. Some people will always prefer the bedside manner a person provides, but many others won't care, and AI will eventually do a good job at imitating a good doctor's bedside manner.
The only way AI is going to replace doctors is if medical technology advances to the point where you can repair a human as well as you can repair a machine (or someone invents AGI, I guess)
There are just too many unknowns and fiddly things going on with human bodies
edit: Haha, I guess Tex's sibling comment makes a good point though..
Most of what the doctor is doing is a type of modern shamanism though. Person doesn't feel good, so the doctor orders a useless test, test comes back negative so the person feels better. Then we complain health care cost too much.
10 full blood panel samples a year with other bio-metric data and a data set of 20 million people to do classification on would crush the doctor over time.
This bullshit health system though makes it impossible to have any real innovation at a mass scale. We will never have personal higher frequency medical data in my lifetime that would actually hugely improve the system and cut most of the cost out.
The hard part in medicine isn't diagnosis and it's not performing the surgeries, it's disease prevention, it's working with patients to find treatment plans they can tolerate, and it's coordinating all of the moving parts (skilled nursing facilities, pharmacies, inpatient rehab facilities, outpatient rehab facilities, durable medical equipment, home health care, insurance companies) to deliver care that results in a good outcome. Where hospital care falls apart is when labs/tests don't get performed in a timely manner and when protocols/standardized treatments aren't followed. You don't need AI to make that work, you need wider adoption of checklists with workflows that are efficient enough to continue to deliver care to the same amount of people while they're being implemented so that hospitals are willing to adopt them. The diseases that can be effectively caught with screening tests - colon cancer, cervical cancer, breast cancer, lung cancer in high risk patients, abdominal aortic aneurysms, hyperlipidemia, hypertension, depression, etc. - already have screening programs in place.
Every dollar spent coming up with the next automated imaging diagnosis model would be better spent on a model that encourages people to get up and exercise 5x/week, quit smoking (or never start), and get their colonoscopy. Once the patient is presenting to the doctor with heart failure, coronary artery disease, carotid stenosis, COPD, colon cancer, etc. the battle is already lost.
Complain all you want about the healthcare system holding data back. You don't need the healthcare system to make the biggest impact on people's health.
—- I’ll add that your shamanism comment sounds like the typical bs that the 20-something software engineer, who thinks they know everything because they make more than 100k a year and have never had to go to a doctor for anything other than strep throat or generalized anxiety disorder let alone spent anytime in a hospital other than to visit family members, that are everywhere on this site loves to say about physicians or other healthcare workers to shit on them.
> Person doesn't feel good, so the doctor orders a useless test, test comes back negative so the person feels better.
Person doesn't feel good. Mild flu-like symptoms. There's a good chance that the patient will get better if I do literally nothing. However, I also know that it could be X, Y, Z... So I order a test to prove that it's not those diseases because if it turns out to be them it would make me guilty of gross negligence.
Concrete example: symptoms of hypothyroidism are similar to depression, therefore you must rule out hypothyroidism in order to diagnose depression.
> 10 full blood panel samples a year
Why? Where's your evidence that this waste of money will benefit anyone? Even yearly screenings are sometimes questioned in medicine and they do have evidence backing them up showing reductions in mortality. What are you even trying to find?
Also, because we haven’t done this at scale, we don’t know the true baseline for most people who may have something on the blood panel samples but never get tested because they are asymptomatic. So then we have this whole group of people with recommended treatment because of the results, even though they are asymptomatic. And they are treated, which then leads to increased costs and side effects…
And now we’ve effectively increased medical costs and decreased quality of life for asymptomatic patients. BUT - if we do it with just a drop of blood, we might be able to start a startup and raise some funding… We could call it Thermos or something…
They are a nightmare. I was part of a huge project to replace a large part of a telecom operators infrastructure. IBM global services ran the operators IT outsourced. The project failed after a year because of them. It was the 3rd such project to fail. The company in question couldn’t bring themselves to realise it had been their outsourced operators fault once again. Even though they had again lost the bid to do said work.
PwC/Accenture were worse. Hire arts graduates because they got a degree from a good university, chuck them on a 2 month coding/consulting course. Happy days $$$
I once went to a job interview at Accenture. I remember the recruiter told me they only considered me because I went to a prestigious university. When I got there, they practically IQ tested me, were rude to me, and never contacted me again even after they said they would. The job was to write GUIs in C#.
Listen up Accenture, I will drink expensive champagne when you go bust, or get bought.
Not getting contacted again was probably a blessing in disguise. They don't really do much, but kind of act like PMs, but aren't very effective as they don't know the business very well. I think they're generally only used when a company temporarily needs like 20 warm bodies to assist with a large project.
I recently left Red Hat for greener pastures. From where I sat, IBM was slowly turning toward wisdom again, having been run aground by its previous few CEOs. I was skeptical when IBM bought Red Hat, but after several years of not screwing it up, I'm pretty hopeful. Now, Krishna is working on streamlining the business and making the rest of IBM more like Red Hat. Splitting off the low performing Kyndryl, and selling Watson, are part of this by cutting obsolete sectors; focusing on getting Red Hat the resources it needs to rapidly accelerate, and on building the talent pool by hiring more junior engineers, are the positive changes working to turn IBM back into a powerhouse.
They make sure enterprises can run Linux that doesn’t “suddenly” (read: with less than 2-3 years notice) break their critical workflows because some component loses support or some dependency reaches EOL - they do this by extended maintenance, backporting (security) patches to old versions, providing tailored support etc.
This is very valuable to enterprises and so they pay a lot for it.
For example, you can still run Red Hat 6 safely and securely until 2024; by that point Red Hat 8 will have been out for 5 years already.
Red Hat is the premier organization doing open source development. They optimize the experiences for enterprises: lots of support and a goal of helping it be easy to use so enterprises can focus on their business logic.
Lots of well-hated projects come from Red Hat: systemd, wayland, ... but they have also contributed well to some other projects which are much less controversial.
Services/products of a company usually bring one of the following to customers: 1) improve revenue, 2) lower costs or 3) manage risks. RedHat is probably mostly about the last one, manage the risks of running linux.
I could be mistaken because it’s been a while, but I read that Watson’s diagnostic capabilities turned out to be mostly marketing and that eventually IBM ended up hiring teams of doctors to process the diagnosis requests that were coming into Watson.
Watson became a marketing term after the company spent hundreds of millions to brand Watson to be synonymous with AI. The term Watson then got appended to existing businesses as it allowed them all to benefit from the brand equity and Watson ads. This unfortunately happened even if there wasn’t any AI capabilities, so it eventually backfired.
Watson Health seems to have been focused on selling the narrative of AI in healthcare, even though the technology wasn’t there.
The divestiture is only for IP also, and it seems most people in the group will be laid off.
As someone with no inside knowledge, it seemed to me that watson started as a technology (or maybe solution/set of solutions) and as time went on, it was pivoted to be a brand? Hard to tell for sure with how difficult it is to get IBM to answer questions about what they actually do...
Worked for IBM for three years, this is accurate. To solve some clients problem we would build an ML solution from scratch just like everyone else, and then try to shoehorn some Watson service into it so we could use the Watson Brand to distinguish our product.
The solutions we built were generally pretty good and our clients were happy, but the Watson part was never anything more than marketing,
Sounds like what happened at Theranos! I read the analysis Watson was generating was ultimately just ignored by doctors because it came to inaccurate conclusions, so that makes sense.
I personally feel Watson was an extremely clever marketing boondoggle. If you think of it, machine learning, neural networks and AI were just making a return into the public mind around the time they announced Watson.
I think somebody thought if they "humanized" AI by making it seem like it was a character, it would make AI seem all that much more closer to the dream.
On the face of it, not a horrible idea, but applied to what was essentially a bunch of separate algorithms.. pretty misleading, but that's just an opinion.
Worth noting that Jeopardy Watson had very little ML and absolutely no deep learning (it was a few years pre-AlexNet). I don’t even think it used any neural networks; certainly not in any major way because they’re not a major topic anywhere in the press releases, working group notes, or the papers published by the Watson research group. Watson was an incredibly complex mixture of bespoke implementations of “classical” AI and NLP techniques to handle questions of different classes by transforming them into search & information retrieval problems. They were able to make it work pretty well for the very limited domain of questions that arise in Jeopardy, but it was also obviously a Herculean task to generalize that approach. I can totally believe that as executives started to grok what Watson really was they realized that it had more value as a brand than as a technology.
Like in Neal Stephenson's Diamond Age with the on-demand voice actors.
I wonder if that was a lack of imagination about what AI will become, or if it was prescience that AI will turn out to be cost ineffective or not capable for most uses.
I have no idea what they got for the money they spent. Merge Healthcare was the most miserable work experience I have ever had. They had patents, I guess, but the actual technology was garbage. And the owner was…a piece of work, let's say that.
The inefficiencies are where all the money is made. After all, patients don’t pay and they certainly don’t pay for results.
Patients may pay for insurance, and buy the right to not worry. Insurance delivers peace of mind by with appointments, papers, and pills. Look at all the bureaucracy and money, it must be fancy and effective. In the course of producing these papers are human doctors, nurses, coders, etc. They sometimes feel a sense of human decency and help people pro bono.
Because they were indicative of Ferro’s “leadership”: flashy branding gimmicks, with nothing to back them up.
Like when he bought an orange Tesla roadster to bring to trade shows. He’d just pop an orange car in the middle of the booth. What’s that got to do with health care? I dunno.
(And this was all a while ago, but this job just always stuck in my craw, because it made “Silicon Valley” feel like an understated documentary and not a parody.)
This is wholly unsurprising. IBM's big play was to integrate data science methods into the workflow. But they approached it from a "we will replace your labor costs" versus "we will augment your labor costs." Besides their AI models being fairly poor in quality, technology doesn't replace people very well where extrapolation is needed. So the quality of service Watson brought was significantly lower than what these businesses offered prior to adoption. So keeping Watson became an exercise in how well the business understands sunk costs and switching costs.
This so much. They basically let Snowflake (among others) eat their lunch. Back in 2015, IBM actually had a good chance but leadership just dropped the ball.
What data was it using again? The blood panel your doctor orders every one to two years?
Medical diagnosis is a trivial problem for machine learning to beat humans. Humans are terrible at this.
The problem is there is not even the concept of high frequency medical data. Imagine machine learning in quant stock trading with samples once a year. Of course it isn't going to work.
The problem is all in the externalities. Doctors don't want AI. They can see the automation path and their bank account change down the line quite clearly. Not to mention most doctors don't know anything about data science so how can you have any faith in the algorithm prediction? No one wants to be the test case and then get a law suit. "I was just following what the computer said was correct".
Wrong answer, pay up.
The real irony to me is in a 100 years people look at the current medical system as complete quakery. Literally have everything right now to build medical super intelligence but stuck with the human doctors doing the exact same things from 50 years ago.
I agree with this so strongly. The medical gatekeeping is absolutely absurd. I can't remember the last time I learned something from a doctor that I hadn't already learned myself with a quick online search. For every visit in the past decade or longer they either told me what I already knew or we were both stumped.
If drives me crazy that I can't make my own decisions about my own health, even for trivial cases. I've spent countless hours and dollars going to pointless doctor visits just to get a routine refill. Literally the conversation at most of these visits is as simple as me telling the doc that everything is fine with $medA, lets just keep it the same; followed by the doctor saying sure and writing me a new script. Such a massive inefficient waste of time.
Yep. Rank and file MDs don’t provide a whole lot of value except to people who are totally ignorant of common illnesses, health issues, or injuries.
If I had the ability to order my own tests, blood work, and adjust the dosages of my meds I could do it a hell of a lot better than the doctor I see every 6-12 months. Antibiotics are the some of the worst with this. The doc literally doesn’t even look at me, I just describe my symptoms and they go “yep sounds like an infection” — like Gods almighty you could be a web form. And it would would actually cost my insurance less which is even more infuriating.
Specialists I have found are actually useful and so I can’t really bring myself to hate that Tier 1 MDs act as a screen for people whose time is valuable.
> to people who are totally ignorant of common illnesses, health issues, or injuries.
Hundreds of thousands, no, potentially millions of people have decided to take hydrochloroquine and ivermectin as a treatment for Covid. The people who believe that they're in a position to dictate their own medical treatment are the ones who most often are "totally ignorant".
Yes, it's more expensive in isolation - in the best case scenario - to have someone competent see a doctor for a refill. But it's a hell of a lot cheaper than the rare case of someone saying "I have self-diagnosed as needing hydrochloroquine for my Covid" and then dying from an overdose after they passed out and their family took them to an expensive emergency room. Your experience is not universal.
I'm not sure that it would be necessarily the doctor that would actually gets condemned in this case. Could as well / instead be the programmer(s) that made the AI.
But this is why the current crop of AIs (which Watson itself might NOT be part of) is problematic : they're too much black boxes.
So they directly clash with the laws that assume on one hand perfect transparency of the tools used, and on the other perfect responsibility of the people using them.
How long before the use itself of a neural network is deemed to have been illegal because it broke one of the laws mandating the explanation of the algorithm that has been used to make a decision to the person that this decision targeted ?
Eventually, way down the line, this might involve giving some kind of civil status to computer programs so they can actually be made responsible.
The technology they sent on Jeopard answered a question, I think, that was looking for the name of a specific king of Egypt with "What are trousers?".
Seems pretty obvious that anything that would do that is not human-like intelligence, and probably the search results should be taken with a handful of salt even if they stuck some impressive natural language generation after it.
I'm okay with this: humans likely make hilariously bad guesses about things that are obvious and easily accessible to machines, and therefore the reverse is also true.
Guessing "what are trousers" for king of Egypt isn't in itself an indicator the whole Watson system is flawed. Although you're right: it's an indicator the intelligence is non human-like.
Just like, from Watson's perspective, a human named John making hilariously bad guesses related to coin flips isn't in itself an indicator that John isn't intelligent either.
Just that there are some categories of knowledge or application of that knowledge that some systems are bad at handling.
> I'm okay with this: humans likely make hilariously bad guesses about things that are obvious and easily accessible to machines, and therefore the reverse is also true.
Yes, it's almost perfectly dual: the things we do easily, without thinking, are hard for machines. Many things that we can only do with years of training, machines do effortlessly.
I think technology like Watson has a bright future when applied in the right way, but I think it's counter-productive to wrap it in anthropomorphic marketing, and especially to give it these direct natural language interfaces. Because that makes people misunderstand what it is.
That's really a choice. I mean most machine learning models wind up outputting a confidence distribution over possible outputs, so it's up to the user to decide how to extract an answer from that. They can and do have low confidence when they aren't sure.
Not sure what you mean by "unfolding". But, unlike Watson, Google Health seems to be building tools that may be useful for healthcare providers rather than just marketing hype.
Anecdotally, the main business value I've seen from ML/AI tech has been in cases where
1. A basic solution shipped and made a ton of money e.g. Ads, Search, recommendations etc.
2. It is financially feasible to have a dedicated team(s) make small incremental progress on these solutions. Even very small gains are beneficial.
3. The business perceives a threat if they fall behind in this area.
The thing is that the gains on the basic solution (heuristics, off the shelf pre-trained CV model, open voice recognition) are pretty small, and if the threat of others making progress goes away - the inferred value of further investment will probably vanish as well.
Other applications which put the AI in the driver's seat (sometimes literally) seem far from production - or if they do work, then they work reasonably well using an alternate approach from what you might expect.
Watson was mostly data science powered consulting pretending to have/be a product. They played heavily on the Jeopardy thing from a marking standpoint but what they were actually trying to sell was a hot mess.
I do consider this a good milestone in getting past the latest “AI” hype cycle and focusing on what actually works in that space. Sat through too many meetings with non-technical execs saying “what if we apply Watson here?”. The likes of McKinsey were pushing this stuff hard in what they were whispering into executives ears.
There should be a way to bet (short) against “projects” or products, not the whole company. When they hyped about Watson Health, I “knew” it will fail.
being cynical is easy because most things fail, the challenge is in identifying winners early or identifying losers after they’ve had some measure of success.
Being profitable is only one angle though. Youtube is the biggest media network right now. I wouldn't be surprised if it beats Spotify as a music streaming service and a host of other unrelated sectors as well.
Yes, I think youtube is making billions of dollars a year. Youtube's revenue was $25 billion last year. It's a mature product. You don't think it's making money?
Google still doesn't release the profit figures for youtube, only revenue. Even the revenue figure was a secret until 2--3 years ago, so it was probably not that high. If youtube was very profitable, I'm not sure why Google would hide it in its earnings since they almost always try to show how they aren't exclusively dependent on their search ad business. I'm not saying youtube does not make any profit at this point, but if it wasn't tiny there's no reason for them not to talk about it.
I mean, the opposite is also true, isn't it? If Google's search ad revenue was going down while YouTube ad revenue was going up, I feel like Google would want to keep that a secret so that people don't realize that search ads are shrinking in relevance.
Basically, I don't see that Google has any incentive to break out its profits by line of business unless someone forces them to. They're better off if you just look at a black box of ad revenue and say "yeah it's all profitable, so ads are as strong as ever."
I'll give a different answer, which is that a blockchain-based prediction market can be used as an oracle for other blockchain-based contracts. So there can be both a final answer and a mark to market for the contract which should approximate reality in some way. However, being unregulated, there's always the possibility of cornering the prediction market and causing the derivative contracts to end with unreality. So you may need another kind of oracle to finalize the market price of the prediction market.
Probably could be accomplished without crypto, but it can also be accomplished on some blockchains with minimal additional investment.
Good question. Prediction markets [1] allow people to bet on outcomes and benefit financially if they are correct.
However, many jurisdictions ban them outright claiming that they a form of gambling and challenging the unregulated nature of questions leading to misaligned incentives (“When will that building burn down?”).
Yet despite these issues, the scheme can offer a neutral ground for betting against overhyped technologies or registering dissent against the policies of authoritarian regimes.
Cryptocurrency based prediction markets further protect the participants by masking or hiding their identities.
The combination of these features makes prediction markets an effective way to deliver global-scale censorship-resistant voting to the masses.
I never said that prediction markets should be illegal -- I'm just acknowledging what you stated, that in some jurisdictions, they are. That's a fact. Running a cryptocurrency-based prediction market doesn't make it less illegal.
Your argument isn't with me, it's with whoever decided a prediction market should be illegal. Go change that person's mind.
Neutral ground is useless if the blockchain doesn't have an oracle to know what happens in the real world.
The blockchain only knows about things on the blockchain itself. So someone has to do the actual data entry into the blockchain, and that person is the weakest link in any 'prediction' scheme.
It will be interesting to see if self driving cars and the way they've been rushed to market with the same brute force marketing will meet a similar fate.
Self driving cars are just that, marketing. Tesla for all their hype have limited driver assist only and even Google who seem to have the most advanced offering only works in limited areas in good conditions and the dataset that drives it requires lots of maintenance.
The general problem is too hard, and general practice has some of the same problems. Probably less adversarial data, but there’s still litigation to be had from confusing an AI GP. Or narcotics.
It's unpredictable enough that it should be considered just "limited driver assist". Only a fool would look at https://www.youtube.com/watch?v=2ub2F-UnXIU and go "yeah, that's full self-driving, all right." Slapping a "beta" label on it means nothing - you could be talking about how Gmail was in beta, or you could be talking about Fallout 76.
Tesla's marketing is extremely disingenuous, IMO. The name of your product creates expectations in peoples' minds, and sure, you can absolve yourself of liability by putting in the fine print "this isn't anywhere close to true FSD and your car might not be powerful enough to support it by the time we get there, so you gotta keep your hands on the wheel," but that doesn't make it right.
If they called it "advanced driver assist" or something similar, I'd be fine with it (it is more advanced than traditional driver assistance tools like cruise control and lane departure warnings, after all). But I doubt they could get people to pay $10k or whatever the current price is if they were more honest. Instead, they would prefer to earn more money by slapping that FSD label on it and letting people immediately turn their brains off.
In aggregate, Tesla’s FSD is demonstrably not up to the task. “Limited driver assist” is a much more fair assessment of what their software is actually capable of than the “full self driving” branding.
Tesla advertises their technology as being on the cusp of Level 4/5 applications but legally (when defending its actions to the California DMV) argue that it is and will continue to be a Level 2 (i.e. limited driver assist) into the future and that FSD beta should not fall under regulations concerning testing of L4/L5 autonomous vehicles.
Perhaps most importantly, all legal responsibility falls on the driver, regardless of the fact that the car can cause accidents faster than a human can realistically react even if paying perfect attention.
Agreed, AI is just like any software. There are good, bad, scammy and brilliant examples of it. With AI somehow though people like to use one bad example as a referendum on everything.
I think I understand why (because AI as a term is overloaded by marketing teams), but the inclination is to paint with a broad brush is still inaccurate here.
Yes. The IBM Rationale suite failed even though it wasn’t AI. It’s the IBM way they commercialize things by going to golf with execs which is the problem.
A friend of mine wanted to show off his Tesla by making it come to the front of the restaurant from where he parked it. Like he hit a button and it was to drive up. It got stuck somehow and was diagonal in the row. He was like “ehh sometimes it doesn’t work.”
AI in general is very over stated. When it works it’s great, when it doesn’t (which is often) then you lose all trust in it.
I think that's the wrong conclusion from this story. The conclusion I draw is that some companies (and Tesla in particular) don't appreciate the "last mile" when trying to apply AI breakthroughs to consumer products.
"The plane lands safely 99% of the time" is an impressive demonstration and a completely worthless product, but if that's all you have then what can you do other than launch it?
It says that (driving) AI is a rapidly changing technology, pushed along by these companies.
The definition of "reliable" here is also important. Usually this devolves into a series of moving goal posts ending with "if it can't do everything perfectly all the time then it's not real!"
It's a fuzzy thing yes. But it is still clearly not safe to drive everywhere with AI. A claim was made by experts and leaders about AI how by now self driving cars would be ubiquitous. That claim was wrong. That does say something about AI. It is a counter claim against the initial claim.
This is kind of funny to see after reading the Tech Review's piece on Watson Health from 4 years ago (https://www.technologyreview.com/2017/06/27/4462/a-reality-c...). They were wrong on the outcome but right on the diagnosis - that the marketing got way ahead of the engineering.
It was acquired by IBM for use in Watson back in 2015. Blekko was an interesting attempt at addressing search engine problems using a thing called "slashtags" to better categorize searches.
Many people shame the startups for fake it until you make it, but IBM with Watson and Watson Health did exactly that for years and 'serious' analysts were predicting how their healthcare AI efforts will increase their revenue.
Wish they had resumed IBM Chef Watson, it was completely useless and the exotic ingredients made the recipes impossible to prepare, but for a while it was my favorite procrastination activity
History will see our current decade of AI and only see over promises and under deliveries.
I have decent amount of hope for AI, but corporate greed, hype by practitioners, a general explosion of various edTech companies hyping up the hype to drive online course sales and general excess of VC money is driving an embarrassing amount of AI failures.
I am sure that any fad now and in the future, will have a similar cycle.
I am aware that a friend's very small company related to NLP/NLU[1] beat IBM in a sale because the algorithms worked better than the Watson ones what seems incredible in two things: beating them at sales and technologically.
A lot of the hope seemed to be in document summarization from the latest medical literature, plus integrating patient data from electronic medical records.
The autopsy of this could be interesting. Some of the critiques against using electronic health records previously was that many of them were designed for medical billing (I don't have a good link, but Eric Topol's "Deep Medicine" has some notes on this problem https://www.basicbooks.com/titles/eric-topol-md/deep-medicin...).
Man, I was so excited by that Jeopardy win. I fired up my Eclipse Prolog and went through a few example from "A Gentle Guide to Constraint Logic Programming via ECLiPSe", http://www.anclp.pl/, and Bratko. It would have been such a win for Prolog if IBM Watson did well. See https://www.cs.nmsu.edu/ALP/2011/03/natural-language-process... for more context
(Of course, that's just a sub-system I'm focusing on; there's a lot more to Watson than parsing).
The team of developers I was on around 2014-2015 was asked to do some user experience testing sessions of a mobile app that was part of our company's partnership with IBM, which was using Watson to answer users' healthcare questions with a chat interface.
In short, we were not impressed, and basically said so in our feedback. Granted, that's just a few data points, and it was internal.
But besides that, the overall vibe I got from the very businessy, very not-engineer management behind the effort was that Watson was brilliant, as demonstrated on Jeopardy, and the main stuff left to do was some plumbing to connect our stuff to some of that Watson brilliance, and of course the business details of the partnership between the companies.
>that GPs in particular would be replaced by a lower-cost Watson descendant
Everybody is trying to replace GPs (and even specialists) with AI.
But I've experienced a massive issue in healthcare that does not need an AI, just a good database.
I was prescribed intensive imunorepresive therapy... and they forgot to put me on preventative antibiotics.
If there was a very simple IF on my prescription (if Medrol > 16mg && TimeOnMedrol > 3 months { checkIfOnAntibiotics() } ) I would not have almost died with a PCP pneumonia.
Engineers always focus on the interesting technical innovation. But we have so much low-hanging fruit still to do, that just needs to use our existing technical abilities in really, really boring ways.
Often I see projects like Watson, Libra, Wave... which makes a very insistent voice say, the chance of this being real is really really small. This is completely anti-thetical to agile.
What is the chance that this makes it through the gauntlet of product-market fit in-spite of the massive marketing dollars behind it and actually becomes a useful thriving product?
I wish there was some way to short individual product or initiatives at tech companies. Perhaps it could create a feedback loop of sorts and actually be useful rather than just being a ego-validation mechanism for the shorters.
As far as I’m concerned the only cool engineering thing IBM does anymore is POWER, which has a sort of unique memory architecture but otherwise is well behind everyone else.
What else did they do in my lifetime? They took a profitable RedHat and gutted it, they took the best Laptop line and sold it to Lenovo and almost ruined it, they tried to be a front runner in ML but blew their budget on marketing (remember Watson on Jeopardy?)
The final straw for me was watching football with a techhy friend and a commercial for IBMs “hybrid cloud” came on. There’s some executive mulling over whether to “go to the cloud” or whether to go with on premises, and they have a eureka moment where they learn about IBM hybrid cloud and they go into a board meeting and save the day. We both just burst out laughing.
IBM doesn’t make stuff anymore. That’s the core problem.
I work in a role where half of our stuff is in IBM's cloud (for decisions made before my tenure). On a day in Mid-November, we started receiving alerts from our UAT and PROD environments. Logged in, all our stuff was gone. Opened a ticket and did some digging and found in our audit logs an IBM SRE had deleted all our stuff. They then told us there was no way to recover and we'd have to rebuild from scratch.
They had apparently been doing some "cleanup" and somehow our site number got on to a list. All our servers, attached volumes, subnets, load-balancers were deleted.
My boss and I spent the next 30 hours applying terraform and rebuilding anything not automated.
Would not recommend IBM Cloud. We are moving off in next 6 months.
so I worked at IBM cloud, and can confirm this. They bought a cloud service, that by itself, and if left alone would been great. Soft(....something...) was the company... then IBM came and changed everything. I remember the SVP / President of ibm cloud showing up... talking 3 hours about how her son is so great and that we should 'follow' his example... after hour 3, man goes and interrupts and asks a question that was "please get to the point of talking about your son".
Few weeks later, massive layoffs, that triggered the warn act. So now I know how IBM works, see first hand meeting, after meeting being totally worthless. I would say stay far away from anything the touch. Just be glad you could move off their platform and not stuck using their platform with their CICD ... else you would be in living hell.
It's not easy to know when is the right time to jump your old trusted provider. At the beginning of the acquisition not much happens. Things degrade slowly because employees take the burden of doing the job for two people. But nobody can be subjected to the stress for too many years.
Big corporations create nothing, only abuse the good faith of employees and the cost of moving providers of small companies. I have seen that happening in tech. When small innovative companies grew they got enough economic power to not have to innovate anymore. Purchase small good companies and drain them is the new business model.
And it's a shame, there was a time that liked IBM, and others.
Gives me the unpleasant thought of how much value is destroyed and lost in these mindless corporate acquisitions. Incentives are broadly misaligned with what we should want as a society, instead investors want a payday as well as founders, and the acquiring corporation wants a fresh coat of paint and has access to the finance that can make it happen and only hurts 10 years later. In the end promising human efforts are destroyed because the rewards for doing so are too great.
OTOH the average startup is garbage held together with duct tape that naturally falls apart without the founding team who created it. By the time of acquisition it’s usually reached a point of technical debt bankruptcy. This goes hand-in-hand with an over-heated sales team pushing hockey-stick growth that will crash back down when those brand-new customers churn at the next renewal - because the product, while nice-looking, is unmaintainable garbage.
Nice payday for the founding team and the ticking time bomb is paid for out of bigcorp’s wallet. They go on to great new things and the eventual demise of their garbage pile will be blamed on bigcorp.
Not to say that large companies don’t destroy value - they absolutely do, frequently - but that the main error they make is not being able to appraise which startups are smoke and mirrors and which are legit. The rest of us are not so great at it either.
> This goes hand-in-hand with an over-heated sales team pushing hockey-stick growth
This seems like just another argument for limiting startup acquires. Perhaps if a big exit wasn't the goal, the company would focus on more long term viability.
Anyway, I don't think they big companies care as much about whether they destroy value, as long as they destroy a potential competitor.
I see competition often being less about the startup and more about which other competing big tech company could buy the startup to consolidate an existing market strategy. I’d more charitably call it “revenue protection” to preemptively acquire them.
Startup acquisitions, in the absence of astoundingly deep due-diligence should probably be placed in portfolios where a 5:1 failure rate can be tolerated. I’m not sure how such an acquisition would be compensated.
It's not just the company internally that want (needs?) those big exits, the whole VC architecture is built around shot gunning out money for the occasional huge pay off.
I’ve sat in an all hands like that before. Literally 50k$ an hour being wasted listening to some guy we’ll only ever see once talk about his sons 18th birthday.
I think it's a power move. Nobody got up and said, "Fuck you, I have better places to be." So they win. You probably thought it was about the business or something.
Owner of the company spent half the meeting talking about how they take their grandkids anywhere in the world they want to go when they turn 16...I look at the audience paying rapt attention and I'm thinking 'this is a little odd'
Then he mentioned the 'merger of equals' and I thought 'this isn't good news'
Also been on one of those. One of the employees raised the fact salaries had been on a freeze for the last two years. Answer from VP doing the all-hands meeting: "My wife also wanted me to buy a new boat this year but I could not"
Mandating it is a power move. You can give folks the option to come back to the office if they so chose, and let others work from home if they want to.
This implies the company has set itself up to do remote work well. Not every company has, not even through the pandemic. Many are still struggling to get back to the performance they were once at.
It isn’t always a power move, even if HN wants it to be; and yes, I realize that’s an unpopular opinion here.
To be fair, it was the general manager’s bosses boss. No body was surrounded by him and by the time we were due another visit by this position, he had been promoted on.
Everyone wanted to be on Softlayer for a time. It was THE hosting provider. I don’t know if they where any good, but the got great press coverage.
Two years ago I had to help a customer debug some weird nginx behaviour, resulting in their traffic spiking at ten times the expected rate. The IBM/Softlayer VPN required that I used Internet Explorer, but it still failed to work. We spend three month with IBM and IBM Cloud consultants to make it NOT work.
IBM destroy everything it buys. They have POWER, their mainframes and associated software left. How that keeps them afloat is a mystery.
Softlayer was solid at providing colo and dedicated servers. But they were never really architected with the cloud in mind. The pivot to cloud came later on. I always wonder why IBM didn't buy a provider like Linode.
Softlayer had the idea of API-driven bare-metal server hosting (as opposed to ticket-driven or phone-call-driven) early on, which was a big differentiator for a while. But AWS came along with an even more extreme version of API-driven hosting and they never caught up.
As an example, most network or server changes you made through the API resulted in an automated email saying your sales representative would be in touch about your order, followed a minute later by an automated email saying the change was done at $0 charge.
I stopped using Softlayer after IBM took over. I still get emails about the daily "incidents" in "IBM Cloud", as well as monthly billing notices for my $0 bill. I don't know my "IBM Id" or "Softlayer Id" to log in any more as it's been almost a decade, so I can't unsubscribe from any of it.
Relationship messages (like incident reports and bills) aren't typically covered by the CAN SPAM Act, but that law's never stopped anyone anyway. I don't have enough fingers to count the number of daily commercial emails from otherwise respectable US businesses that don't include a mailing address or don't honor opt-out requests. Cold sales mails from tech startups are a big offender...
We're a pretty small org, and not sure we have the organizational heft or resources to do so. That being said, the $1k discount they gave us for Nov based on the broken SLA (resources down) was kind of a slap in the face. We had our minimal core services up in 16hrs, but recorded about 100-120 internal engineering hours for config, testing, and other fallout +1 month.
When we opened the initial ticket, the IBM engineer kept saying "you should ask X why they deleted your stuff". Eventually after attaching the LinkedIn page for the IBM SRE in the audit logs, they realized something was screwed up on their side.
For breach of contract and negligence, IBM were successfully sued, and then banned from all future projects, by the Queensland government in 2013. [0] Which sets you up with a nice precedent and set of documents to see their angle of attack.
> IBM will not be allowed to enter any new contracts with the State Government until it improves its governance and contracting practices.
With that ban _still live today_, it astonishes me that any corporation would trust the organisation to actually carry through with their obligations. You have to really, really, royally screw up for a government body to consider you anathema.
The old adage of "No one was ever fired for hiring IBM" is no longer true or reasonable.
> For breach of contract and negligence, IBM were successfully sued, and then banned from all future projects, by the Queensland government in 2013. [0] Which sets you up with a nice precedent and set of documents to see their angle of attack.
I mean, yes, but also think about how long a government can afford to have their lawyers pursue a case like that. If you don't have those kind of resources, it's a lot riskier.
They also have a very significant interest in pursuing it, in that they often have to follow procurement rules that prevent them from excluding vendors without good reason. If you think a vendor will be a problem in the future, getting a legal judgement in place may sometimes be necessary to save a lot of grief that a private company can avoid by just privately and quietly blacklisting the vendor in question.
In civilised lands the loser has to reimburse the winner's legal costs, so at no cost. If you don't live in civilised lands, well you have other problems.
I'm not sure that is as civilized as you think it is. Loser pays discourages any small company or individual from suing because the cost is too great if they lose.
Even AWS contracts are vague enough to not make this a slam dunk. They pretty much explicitly say if you don’t store stuff in multiple regions you are going to take outages/data loss.
Does your civilized legal system also force the inevitable loser to front your legal fees while the case is ongoing? Or is it possible the plaintiff with deeper pockets can just stretch things out until the legal system has bled you dry and you must withdraw?
I was surprised by some companies too, until I worked outside of tech.
The whole rest of the universe needs software too. Most companies are grossly incompetent to develop it themselves. Most are things that SWEs of the type which visit HN would never, ever want to work on. IBM does that adequately well. That's "services."
If I need a tool built which will manage workflow at a management consulting firm, a custom tool for managing cases at a law firm, or some custom supply chain kludge -- the 99% of other "boring" software -- and I happen to know nothing about technology, who do I turn to?
IBM isn't a bad choice. It's a major step up from Indian firms in terms of both price and quality. It has significant in-house technology to leverage. It's a safe choice. It will usually do better than in-house IT.
I recently evaluated the business of a company which builds ships. They developed software in-house with an IT staff who weren't qualified to tie their own shoelaces. They had huge military contracts. They didn't subcontract to IBM, but it wouldn't have been a bad choice.
> IBM isn't a bad choice. It's a major step up from Indian firms in terms of both price and quality. It has significant in-house technology to leverage. It's a safe choice. It will usually do better than in-house IT.
Having been there, I can say that IBM is no different than the other Indian tech firms like Infosys, Wipro, HCL and other. Infact, there is a rotating door of employees among IBM and other Indian firms.
1. Since the last 5 years, IBM has more employees in India than in the US or any other country [1]
2. Secondly IBM pays more that the Indian companies in India to poach employees but shortchange their US counterparts. [2]
Infact, the only difference between IBM and other firms is that the initial sales procoess is handled by American counterparts. Once the sales piece is done and the actual project starts, it is replaced by the offshore team.
Honestly, I’m not sure IBM is a step up from the Indian firms. It’s certainly more expensive (like, ridiculously so) for not much more quality, if any.
Is it? Really? No. In fact it's not. Name one Indian company that ever reached 1/10th of what ibm had so that it's a candidate for seeing it on the way down.
A serious insult because it'd be much more true would be to look at it's OD, culture and demise since Gerstner. Gerstner wasn't happy with a lot of IBM slop, paper pushers, and corporate BS either. That'd keep it on track rather than spurious comparisons.
Gerstner layed of somewhere around 20% of work force, sold off tons of ibm art, real estate etc because IBM was lost ... And losing money. That says something. Spurious comparisons don't.
Labeling IBM bad because it out sources to India is a vieled insult to indians and it's culture I guess. If that's the position -- not mine --- have the galiteantry and courage to just say so.
I'm reminded of the Futurama line: do you idiots where you're from? Nobody nowhere can say no to that. American culture, OD, and common sense when it's not losing money, playing golf, splashing around shareholder cash on art or tieing up innovation in BS (all of which IBM did pre Gerstner and was called out for) expects problems fixed, brings out the best in all comers, and expects comers to be value add. Thosr that cant play that game are out.
Regrettably this has one dark corner. Management isnt so good at overseeing itself. So in really bad situations they are good at shifting blame. Well nobody said it'd be easy. Let's start by not gossiping however.
> Name one Indian company that ever reached 1/10th of what ibm had so that it's a candidate for seeing it on the way down.
I'm not sure what your point is here, but based on Forbes 2000 for 2020 via Wikipedia [1], by market cap Tata Consultancy Services and Reliance are both larger than IBM. Both have grown faster than IBM since 2020. In terms of companies overall a number of other Indian companies are larger than IBM.
If you look at infotech alone, Tata Consultancy Services is the one bigger than IBM, and Infosys (>50% of IBM market cap), HCL Technologies and Wipro are all larger than 1/10th of IBM.
2020? Big deal. IBM has been around for serious time. Like I said show me an Indian company that was a tech giant for analysis on the way down. No doubt IBM has got work to do. But tata ain't no ibm. Furthermore my take stands up for Indian know how not crapping on it as others have done here. It's just that indian companies nowhere near have ibm corporate legacy. As for ibm: it wouldn't kill you to try to innovate again not react and buy innovation even if Watson was a bust
Tata is nearly half a century older than IBM. IBM is older than the TCS subsidiary, sure - TCS is "only" 54 years old. But I have no idea why that matters to your argument as it's still not clear to me why you were making the comparison.
That said, IBM does today have more employees in India than in the US, and IBMs current CEO is Indian-American, born in India and educated in part at an IIT so I can see why some would describe it that way. To me at least there's no value judgement - positive or negative - attached to that. It seems like you took offence at the comparison of IBM to an Indian company, and I can see why you'd think so in context, but I don't see why that justifies downplaying the success of companies like TCS.
> Like I said show me an Indian company that was a tech giant for analysis on the way down.
I still have no idea what you intend this to mean. TCS is a tech giant. It's the largest IT service company in the world.
As for Tata being no IBM, you're right, Tata Group is older and several times the size of IBM. The Tata Consultancy Services subsidiary alone is larger than IBM, and Tata as a whole employs about twice as many people as IBM, most in TCS. IBMs original business was thematically closer to what they still do today, I guess, but only marginally.
>> Like I said show me an Indian company that was a tech giant for analysis on the way down.
>I still have no idea what you intend this to mean. TCS is a tech giant. It's the largest IT service company in the world.
What is so tough here understand here? I've done IT for 30 years. I don't think I've used a gadget, O/S, compiler, cloud resource, dev-ops, or distributed algo from Tata once. IBM? All day long. I consulted at AT&T ... man the number of things they made I used was insane.
Moreover, given time all large companies cycle between running on all 8 cylinders to periods where marketing, paper pushers, corporate culture BS, losing contact with customers and customer satisfaction, poor quality erode the top/bottom line, lead to a loss of market power, pricing power, and so on.
Tata, assuming it ever had the towering heights IBM hit on all fronts, may be big now. But wait around long enough and Tata like most large human organizations will fall from grace too. And I bet, at it's core, outsourcing will not be found to be root-cause; related perhaps but certainly blaming the outsiders isn't wisdom. So as I said, then re-said, and say again show me one of those Indian companies *who are on a down cycle now*. The way I have contextualized it here makes for a relevant comparison.
While I'm at it: I'll say again unlike posters earlier up, I refuse to crap on IBM because it out-sources to Indian companies. Like anywhere some Indian companies suck. Some don't. Some may be on a high cycle like Tata. Those in the US doing the outsourcing maybe already sucked before outsourcing began. It's those kinds of spurious insults which are not appropriate and not my position.
This assumes that IBM's core business is the same as their Services business. I doubt they have any overlap. They got onto the bandwagon after seeing how successful some of the early Indian services companies were (in terms of revenue) such as Infosys, Wipro, and TCS.
I would put the IT services business of Accenture, Cap Gemini, and IBM in the same bucket as the rest of the Indian firms.
There is a world of difference between a US ship building company outsourcing to India and a US tech firm intermediating that transaction:
- A US intermediator can know the climate in India and navigate the cultural differences because they do this day in day out.
- A US tech company can properly vet whom they're subcontracting to because they have engineers in-house
- A US tech company will have a contract in US jurisdiction. If there is e.g. a data leak, there is liability through US courts. A step down from that, a US company can have US-based oversight and escalation mechanisms
- Social networks and relationships matter too. If you're working with Bob from the golf course, and his company messes up, you'll see Bob again next month at the golf course and chew him out.
... and so on.
I'm not suggesting you or I (personally) should subcontract through IBM, but for a US-based non-tech firm, it can make a lot of sense.
To flip this around, whom would you rather hire to do your accounting (presuming you're not an accountant and know nothing about accounting):
- A US company which outsources to India
- A random company in India
I would go for the former, since I know there would be liability if they messed up, and they'd make sure the US tax code was properly complied with. There's nothing wrong with the latter, but I'd have no way to vet them, and if they messed up, no recourse.
My stepdad manages a team in IT for a very large, very slow company in the banking/financial sector. The decisions about what software and hosting solutions they'll use are made by execs at the upper echelons, probably over games of golf by people who don't know that much. They just know, "I really like Jim over at IBM, he's got a real swagger to his step" and "other big companies are using them" and "hell they just bought a Super Bowl commercial." So a $2M deal gets done, and IBM stays in business.
I spent 10 years at a small (<80 people) CX company that was full of intelligent, motivated employees. We were smart and quick and lean and did very good work. But we never dragged in big deals because no one at the company had that swagger/access to high-levels. The scenario you describe is dumb and ruinous and, unfortunately, true.
Big deals can really put a company in danger. If the company you work with closes or cuts the deal or whatever you could loose half your revenue. On top of that big clients can be really needy especially dinosaurs companies that aren’t nimble. They take forever to pay, have lots of meetings and unreasonable expectations and expect lots of free stuff and service because they are incapable of processing Non standard invoices due to internal politics. It’s a mixed bag to deal with the big guys
I saw this play out first hand: a local digital agency run by a friend essentially ended up "captured" by a major player in the aerospace industry, to the point that 65-75% of their business came from $BIGCO. They grew by 100%+, had employees flying all over the world to set up for trade shows, and were making money by the truckload.
Then Covid hit, nobody wanted to fly, and $BIGCO took an earnings haircut and decided to cut back. My friend had to let dozens of people go. It ended up costing him his company because he'd neglected bringing other work into the pipeline.
Yep that’s super dangerous especially cyclical industry like aerospace. Plus aerospace companies are notorious for paying late are having unreasonable demands.
Coworker dad went from being a millionaire to living in a truck this way too.
While that's true, the execs who make these decisions usually don't care about the actual implementation. Once the deal is done, it falls on their "IT division". And two things happen: Jim over at IBM still pampers the exec with a dinner or two. And the exec also suspects that some, if not most, of the problems are with his IT team.
Big companies have very strong anti kickback rules. You can get around them through board level connections but not much sort of That. Nobody Is risking 500k a year compensation over a dinner or 2.
100% agree. I know many capable developers who will never do anything other than close tickets because they cannot build relationships. Some of them do not even understand why building a relationship might be fruitful.
Big corps tend not to do deals with small corps. They don't want the small corp to become dependent on them. Simple contract termination becomes costly and litigious otherwise.
I've worked as a sales engineer/architect in teams selling to people like your stepdad's execs for almost a decade. I can 100% guarantee the sales reps and their leadership constantly practice "swagger" and remind each other of its importance. It's hilarious.
I think what many people don't realise is the insane amount of research that is being done at IBM. In lots of areas, I know of quantum computing, silicon photonics, process development for integrated circuits, processors... They still file the most patents per year in the world by quite a margin (9000, the only one being remotely close is Samsung at 6000, for comparison apple and MS have 3000) and while I am not a big fan of patents, I do realise that one has to do significant research for getting this amount.
They probably could just run much of the business just on the licencing fees they get. If you think they are not doing anything you're likely not their target customer.
I think they still make a lot of money from their legacy business, z/OS & mainframes, DB/2 etc still run basically all large banks, insurance companies and many other types of businesses. IBM can charge whatever they want for the hardware and services to support these things because their customers have no alternative. So they have just been farming this for decades, and can afford not to succeed at anything else (so they don't).
No one talks about Oracle. But they're still around. We did a major tech project to migrate off of Oracle after an acquisition of a large org that was running it.
It was a year-long effort to migrate. But it was worth it since Oracle renewal costs were going to be nearly 50% of our IT budget.
I did a similar year long migration off Oracle. What helped were all the automated integration tests that had been built previously. It made it so much easier to verify that everything would work after the migration.
Oracle is also arcane, buggy and poorly documented (the buggy really surprised me when I first started using it). And there are much less resources online compared to the other big databases.
I’m not sure about the architecture, but airline booking is very complex. You basically need to support a traveling salesman algorithm. It’s also one of the original use cases for large scale computers. The Sabre airline booking program dates back to the 60’s so it’s also very legacy. The Arstechnica article (below) has a good history of the original military program and how it helped to spin out airline booking.
Modernization for these systems was probably long overdue.
I recall talking to people who worked at a company that competed w/ Sabere/IBM
There was a project they did not want to do. To avoid saying "no" and risking the relationship they quoted what they thought was an outrageous price, expecting to loose. The customer said yes. They had underestimated how much IBM had been gouging them for so long.
It's kind of similar in some ways to the traveling salesman problem. Which is not considered np-hard.
"How do you get to tokyo from paris", the cheapest, the shortest time, the least layovers, add a stop in X, etc. Not that easy.
Then you have to remember all the stuff under the hood like how are you caching all that information, how do you actually register the sales of all those tickets. Are they in your flight alliance? Are they goign through your regional airline systems too?
I would never want to touch that stuff. Way too hard. Way too many legacy systems powering it too, probably.
Every single airline they ingest probably has a phone book sized list of special cases and edge conditions that are distinct and unique. Multiply that by every airline on the platform and every consumer of the dataset and yeah… it’s incredibly complex.
Not to mention the uptime requirements and other SLAs in place (which probably are all different for each contract they sign)… yup. It’s probably a monster.
They make money on those who have more than they know what to do with.
Case in point: I spent six months in a project, which at its peak had about forty people working on it. Eventually it was scrapped and replaced with a solution from IBM, which in turn ended up... not being used at all.
Overall it was a hilarious waste of everyone's time, but somehow that was okay.
Similar. Worked on a project where there were 50+ contractors to automate simple biz workflows. Run that for a few years @ their rates and you'll see how much enterprises spend on relatively simple software projects.
I was part of that acquisition. To be fair, Weather Channel was already running Weather Underground into the ground when they acquired it first. IBM just came in and helped them finished the job.
A huge part of it was the incompetence with which IBM pushed us to use Watson modules in our products, which I could see 6 years ago were worse than open source AI options and had no application to Weather Underground's services. They were basically toy projects being advertised as ground-breaking AI. I'm not surprised at all to see Watson finally collapsing under the weight of its vacuous claims.
>> They were basically toy projects being advertised as ground-breaking AI.
They were media events that lead to powerful media events, which in turn lead to investors pumping money into the stock price. Shareholder value is the only real profit. Watson being on Jeopardy no doubt garnered investment dollars from thousands of wealthy retirees. Those toy projects earned their keep many times over.
I don't mean to inject cryptocurrency cynicism & NFT skepticism into this discussion about IBM Watson...
But as someone who doesn't know the tech, but worked in the media side as a vendor at the tail end making marketing materials for IBM during their "Internet of Things" craze, I couldn't help but feel, as a laymen, so excited at what IoT (and other crazy developments like Watson) could be, because apparently IBM at the time was hitting up a buncha different vendors and just blanketing a certain sector of the marketing industry with jobs. Any colleagues I talked to were on some IBM marketing job or another.
Fast forward to about 7 years later, and I still have no clue what IoT is or does, but I sure saw a buncha marketing material flood mainstream media for a minute, with IBM saying it'd be revolutionary!
Just makes me think about web3/ crypto/ NFT's, how it's coming down hard with media campaigns, claims, yada yada. Definitely seems about hype & optics, just like IBM in their IoT media carpet bombing era.
This is a great insight. Even if execs know $x billions will be wasted on such trendy projects (toy projects to those who know what’s going on), they will still go and spend $x billions. Why? Since it keeps the market cap going up. This positive delta in the market cap is almost 10 times more than $x billions.
It is even worse than it looks considering the opportunity cost of not sticking the money in basically risk free and cost free SP500 ETFs. Even Warren Buffett took a huge bath on IBM.
They completely destroyed the iPhone app. It’s been, what, more than a year at least and the new version’s hourly forecast still shows the beginning of the day (1am) even if you look at it at 7pm. So many things about that app that made it great got ripped out.
I worked breifly at IBM research last century. The spent a lot of money on research (6 Billion). software, chip design and algorithms and a lot of just basic research.
But when I left to go back to school "global services" a business to business consulting division was the big up and coming division. It seems that division is where IBM decided to go. Honestly they'll just sell to some big businesses so likely you'll never hear about what they're doing.
I'll agree they seem to have lost their way. Its a shame really. They did some good things: I remember a lot of the engineers there would travel to schools and promote engineering careers.
Extremely reliable, and extremely good at what they do.
They sure are expensive.
A lot more companies should adopt them.
Yet its going the way.
They run at scale at a lot of companies.
AS/400 / iSeries was awesome at least in the beginning.
I think it may be discontinued now.
Those machines were extremely reliable and well made.
Often companies who had bought one had no idea where it was.
Someone had set it up for them 7 years ago and after that nobody
paid attention.
Some places were better and did proper backups.
Which means stuff the right tape of a rotation into the slot.
They would also call home to tell IBM of a proper that is developing
and they would send a tech out to switch the parts prior to anyone
using it had any problem.
(and that is when the machines were sometimes hard to find.
One was buried in a closet, with tons of paper cases, paper archives.
stack buttom up to the floor.
I wish there was a way to learn mainframes that were accessible to mere mortals. Some toying around with a (almost certainly illicit) emulated copy of z/OS revealed an extremely complex, no doubt powerful, but entirely alien system that I'd have loved to get my head around, but alas, I could find no good resources.
They also do a lot of reselling. They will pitch some sort of cyber security upgrade to their client and after the client signs they will ask Akamai to onboard that client
That was the biggest problem. It wasn’t quite possible yet, at least with how IBM wanted to use it. Rometty and her executives believed their own marketing hype. It’s why, billions of dollars later, Watson Health failed because it couldn’t make better cancer treatment decisions. Watson Talent Management failed because it couldn’t make better hiring decisions. The tech was misused.
As a worker drone who has spent my career in Sector 7G, I'm continually amazed at how many business decisions seem to be based on these "magic" quadrants. We spend 12 months building a capable and flexible infrastructure on Product A, only to have our management ask us why we haven't moved everything on to Product B, which is slightly closer to the top-right corner in the magic quadrant.
I always answer, "Sure, we could, if you're fine with not other progress getting made towards your business objectives for 6 months."
A former employer tried for years to get onto the magic quadrant, and never succeeded. Until they started paying gartner for access to their “specialist knowledge”, and suddenly they were on the magic quadrant … in the lower left, with gartner pushing them to pay more to get better access.
I set up briefings to Gartner Analysts seeking to get our consultancy on a quad early in the mobile era.
One of them was on the earliest examples of hybrid HTML / native views in iOS. One of our engineers was implementing them in the Apple Store app.
IIRC, Gartner was not ready to split out boutique mobile dev but getting an earworm into an analyst with influence over a quad is still valuable.
I presume there is chatter on potential forming of quads before they make print.
Working these executive-influential information sources, and our firm continuing to land major app dev contracts led to an acquisition by Deloitte Digital.
Hmm... maybe the magic in magic quadrants is in how they attract the sorts of people that will act on the information conveyed by the grid. Way better than an Ouija board for IT recommendations. Ouija is very hit and miss, really depends on what spirit you get connected with. Magic quadrants just work.
They are in the audit business. Large companies have pockets where outsourced engineering teams have installed or forgotten to delete their outmoded software. They send in an audit team, and come up with a massive payment due. Then they negotiate with their “customers” to have them buy new software for approximately half the cost of audit payment. IBM gets new revenue (and new products to audit) and companies pat themselves on the back for averting disaster. And the new software never gets used.
Most big tech companies got out of or significantly scaled back their blockchain business, it is solution chasing a problem. The web3 people apparently haven’t caught on yet
I think secretly they are aiming for the digital currency aspect of blockchain, e.g. Bitcoin but couldn't understand how it works as MBA schools havn't mint out bitcoin graduates yet. Maybe in abother 10 years.
The problem is infinitely printable FIAT, controlled by corrupt and incompetent politicians that is very slow and very expensive to to transact overseas and mutable.
The solution is 100x faster, cheaper, more secure, immutable, less prone to fraud and limited in supply.
Those are problems in theory, but I don’t think most people are concerned or affected by them. I’m certainly not.
I never need to transfer money quickly between accounts — it’s never once been a problem to wait a couple days. And sure there are real economic problems with printing money, but again, the government does a decent enough job at keeping the dollar stable that it doesn’t affect me.
And there’s the fact that the US gov has tons of power to maintain the validity of the fiat dollar through legislation, and as a backup they have the use of force through police and jail (in the case of tax evasion, or avoiding the laws). Then there are international alliances, and there’s the largest military in the world also with a strong interest in maintaining the dollar’s value.
So I’m not worried about the value of the US dollar in the long term — at least I certainly trust it more than a purely technical solution with none of the US Gov benefits.
Faster: I don’t have any problem with speed of USD transactions. In fact, most transactions are faster than crypto via credit cards or cash.
Cheaper: there are $0 transaction fees for cash, and low fees for credit.
Secure: US laws do a decent enough job
Fraud: crypto exchanges get hacked and there is often no recourse — if my credit card is stolen, there are laws that protect me
Limited supply: by definition, that makes the currency deflationary, which is horrible for a growing economy. And it’s obvious in bitcoin. Nobody spends money today if it’ll be worth more tomorrow — that’s why everyone just buys and holds bitcoin as an investment, not uses it as a currency
You’re saying that you trust the government a lot in making sure the dollar value stays stale, however, it has lost 30% or more since the start of the pandemic if you look at price increases of commodities, so you are already very wrong.
It might not matter to you that sending cross border transactions have very high fees, because you live in a first world country and are rich, but 99% of the world aren’t as rich as you.
They have a product called Hyperledger Fabric that is marketed as an enterprise-scale permissioned-blockchain. I’ve tried to get it working before with some free credits and couldn’t figure it out.
IBM identified back in the 70s their core asset and were very explicit about what it was. "No one gets fired for buying IBM." Their key strategy since then has been to monetize this asset in a variety of creative, and mainly very effective ways.
Thinkpads were a great example of this. Laptops which promised decent quality and support for a high price. When the laptop market was demystified and commodified, IBM correctly got out of it - for a decent price.
If some random start-up, or even Google, had built Watson, it would have correctly been seen as a gimmick. Instead it sold literally billions of software consulting to people who thought they needed AI but actually just needed a search box with dynamic autosuggestion. Would you rather get some junior guy to hack something together using open source tools, or would you rather pay IBM 50 times as much? If you chose the former, you're simply not in the target market.
The hybrid cloud is exactly the same game - as is made quite clear in that ad, it's pitched at middle management who don't want to look like chumps for ignoring the cloud, but don't want to fuck up by moving to it.
Reputation is a difficult asset to monetize - effectively you make money from it by degrading and then destroying it. After all, if you carry living up to your good reputation, you're not extracting any advantage from it. IBM can't sell their reputation or their name to the highest bidder. All they can do is keep trawling for business lines where it gives them a comparative advantage.
It's easy to see this as unscrupulous - but their customers genuinely do get a benefit from the confidence they have in IBM.
I understand why you're saying this. I have no idea either. However, open their 10-K and you'll find out how they make money. In fact, while their revenue and profits are declining, they still make more than $70B in revenue a year with a profit of about $4-5B, so their ability to stay in business is higher than many tech companies that are not profitable.
IBM is old, it's good and bad (probably not the first time they made bad decisions). Let's see if they can wash off the last decade or two that were full of mistakes.
They still do stuff but it's hard research and niche so business wise it won't make them short term success. You mention power but they also have a good hand in Quantum Computing.
I'm a Red Hatter, and I'm not sure what they mean either. I obviously only know my own little corner of engineering, but I've seen no signs whatsoever of being gutted. From where I stand, it's just a change of ownership that, at least for now, is completely transparent on the ground. I expect the situation to continue for as long as Red Hat keeps making money.
They haven't. I have no doubt that IBM has historically mishandled a great many acquisitions but thus far I haven't seen any changes that feel pushed by IBM.
Source: I work at Red Hat.
It's a bit of a strange comment considering it blames IBM for Lenovo's management of the Thinkpad line and a commercial that they later realized (but still haven't corrected themselves) was actually an HPE commercial [0].
Before IBM purchase: Travel to clients, build and/or fix their things, suggest improvements.
After IBM purchase: Travel to clients, build and/or fix their things, suggest improvements.
At least from my side of Red Hat I've experienced zero changes in how I go about my work. In fact, my schedule is even more packed now, we can barely keep up with the demand. As far as I can tell IBM has left us alone to do our thing. Maybe it's different for other departments.
Longtime Red Hatter here (in a non-engineering role). No "gutting" has taken place whatsoever. Thus far IBM has had an almost entirely hands-off, do-things-your-way, noninterference-in-internal-affairs sort of approach to Red Hat. That's not to say Red Hat hasn't had challenges but those likely would have developed even if it had remained independent.
That's a joke. If you read that drivel prepared for the stock market, you would come away thinking IBM is the biggest Cloud operator in the world. In reality of course they have just rebranded all kind of cash flow streams as "cloud" - because they know "cloud" will make the stock go up whereas "mainframe" makes it go down.
They also provide mainframe-based Linux VMs for clients that require the encryption technology built into those machines. If you need to give certain assurances by law or contract, they may be a good option. Apart from that, if you need on-demand VMs for IBM i or AIX, they are one of your only options.
IBM has acceptable tape systems.
Would be nice if they did not keep changing tape buffer sizes/times and other conditions without properly advertising the changes, but LTO is bad at scale so they have that going for them.
Another insult to the injury: they were doing e-commerce with WebSphere Commerce series as early as 1998, yet they could not even go beyond the limited presentation-controller-db tiered architecture, and could never imagine something like shopify.
They have a very big consultancy business. Probably has a much better brand name than say Tata consulting. Plus their products like db2, websphere or openshift have thousands of businesses locked in.
I don't think they do either, judging by my experience working there as an upper-level-support technician 15 years ago.
It seemed like the organization was book-ended with decent brains: engineers and front-line managers were decent to fantastic, and the upper-management seemed to be decent at the time. However, both ends seemed to be choking to death on a hundred layers of middle management. 7 years after Office Space was released and I actually had three(3) managers. Three! I had a technical manager with whom I had bi-weekly meetings where we talked about nothing, a non-technical manager with whom I had monthly meetings where we talked about nothing, and the head of my department who was the only one who meaningfully managed me in any way. (And he was absolutely fantastic.)
For example— they made some big announcements about their impending migration from windows to linux for everybody from admin assistants to sales to developers. Exciting! I loved that linux was getting more professional credibility, and my product ran on Solaris, so having a local UNIX environment would reduce some of the cognitive load for networking, scripting, etc. etc. There was no internal mandate to start the migration yet, but I was too eager to wait. I found the official image on the intranet and started writing documentation for my coworkers. It was pretty smooth! The complex GUI apps like the Lotus suite worked great! Well, as great as they did on windows, anyway. The installer was quite polished! I was excited!
I had one more thing to install— the ancient, internal defect and ticket tracking clients used by every technical worker, product designer, all of their managers, etc. Neither the intranet page for the clients nor the Linux image docs had any info. Hours later, I found a months-old internal note EoLing the Linux port, directing people to use the obtuse CLI instead. No problem— we're all technical people here, right? Problem. The API used by the GUI client supported necessary functionality the CLI didn't. That alone rendered the Linux initiative dead-in-the-water for most technical workers who'd benefit most.
I'm sure the manager who canned the Linux client was solving a very real problem, but a) a decision directly affecting company-wide strategy getting lost in the ether, and b) nobody checking to see if these big overtures were even basically feasible, embodies their organizational shortcomings. (I might have gotten some of the details wrong— it was a long time ago— but you get the gist.)
That's almost certainly why they're getting sued for purportedly blatant age discrimination, too. Managers in the middle with too much sway to have that little top-level visibility solving their problems using means that end up screwing lots of people.
That they style themselves as a technology-focused business consulting company rather than just a tech company is pretty rich.
I don’t think “doing cool engineering” has anywhere near as much to do with staying in business than you think it does. And IBM of all tech companies is the one that always was more about suits and sales than technology.
The tech sector prints money. Large companies can leech off past heroics built by former employees for decades, even if the current employees are incompetent. A zombie company if you will.
HPE is kind of even more baffling. They make generic servers while, at least, IBM can sell you a brand new POWER 10 (running AIX, Linux or IBM i) or a mainframe. A new generation of mainframes is due this year and the crazy cache architectures they have shown last year is quite unique.
Thanks! I think the commercial is ok, at least it makes an attempt to explain what the product is. The IBM "hybrid cloud" commercials I found on youtube were just awful.
There's still a phenomenon in advertising where it increases your awareness of a category, but you don't correctly ascribe it to the correct advertiser in that category. So funnily enough, I could still see someone going to IBM based on this ad.
I imagine IBM quantum computing will go to same route. IBM has become a husk of its former self — mostly marketing, and generally 5-10 years behind the cutting edge.
Good riddance. The number of smart people who expected me to comment intelligently on Watson’s plumbing in the before-times was disturbing. Trying to be very polite when saying “I have no idea what Watson does, and I’m not sure you or the person you talked to does either” is ... not my strong suit.
It wasn't a product. It was a business unit created by the acquisition of (at least) 4 separate companies that had wildly disparate products, data sets, and consulting teams. The only thing they had in common was the focus on healthcare (and even that could mean anything vaguely related to providers, payers, or life sciences). "Watson" in general evolved into little more than a branding that was applied to anything remotely related to AI, analytics, or data management.
It was just IBM throwing stuff at the wall to try and keep up with big tech companies. They have been in decline for a long time, and I assume this marketing stunt did not fool anyone actually involved in the businesses of healthcare or tech.
I think "Watson" was never a thing (a technology or a product). Rather it was a marketing term. "Watson" meant any solution or research project that was developed by IBM and had remotely to do with AI.
A bit like "Active*" or "NET" back in the day for Microsoft.
I worked on a project 4 years ago using some of Watson's cloud services (Its more a brand than a product now). Worked ok for us, certainly on par or better than Google / Microsoft's offerings at the time. We actually had contact with some of the original Watson team, that had some interesting insights / details - needless to say, much of Watson is 'brand marketing' and not really hard AI science ... bit like every other 'AI' product in the market right now I guess
- Disclaimer: I work for a cloud software company building AI products ... ;)
The business is being sold for an undisclosed price to Francisco Partners, a private investment firm.. Watson Health was set up as a separate business in 2015. IBM then spent more than $4 billion to acquire companies with medical data, billing records and diagnostic images on hundreds of millions of patients.
I don't know if I'm the only one, but I always felt like Watson was roleplaying being a relevant tech company. Something about the way they marketed it just seemed like it was a big PR campaign with no meat behind it. I always had a suspicion that most people agreed but was never really sure.
"billed as a revolution in medicine" by whom? IBM's marketing department?
Anything "Watson" (together with 95% of that company - optimistically) is marred too deep in bureaucracy and yes men to do anything productive and innovative.
back in 2016 I joined my first company as Fresher and was excited to work in the use case of Ml and was given my first project for making chat bots using IBM Watson Conversation :P
I think that is the worst project i have done in my life till now.
The only real business problem is they didn’t program Watson to do what the Healthcare industry actually wants — make more $$$$$. The last thing they want is a computer that can actually diagnose people and provide effective solutions.
> The last thing they want is a computer that can actually diagnose people and provide effective solutions.
Intimately knowing the non-profit side of the healthcare system as well as the construction and operation of data science systems, I wholeheartedly disagree with your assertion and your conclusion as being a general takeaway.
The parent comment assumed that everything in healthcare is profit-motive driven. However, there are large portions of the healthcare industry that are non-profit, that are transparent in their funding and their costs, and that are looking to implement AI to improve healthcare outcomes. Parkland Health and Hospital System, Harris Health System, University Health System are some that I am more familiar with that run with this (PHHS recently achieved HIMMS Level 7 certification, for example). These are social safety-net hospitals and healthcare systems -- they care for everyone regardless of ability to pay. They focus not only on emergency and inpatient care, but also ambulatory care, primary care, and even fund (at arm's length) community (non-profit) medicaid insurers.
On a more subjective side, I've seen a lot of folks out to make a buck, but the non-profit healthcare side has been much more focused on patient outcomes.
IBM is such a shadow of what it used to be. Hopefully newer health+genomic+ai startups or initiatives at less dinosauresques companies will make the next leap happen in our lifetime.
I attended a talk a few years ago given by one of the blockchain VPs at IBM.
It turned out that under the hood they were just using conventional distributed database technology. All marketing in order to get multiple companies to work together on shared systems.
I agree when thinking about building software in one org where there is coordination. When expanding to multi org and international, the problems to solve become much clearer imo.
Federated, hashed data stores in zero-trust environments is one (though this isn't the best or only way to approach it, and blockchain is almost always unneeded), where you don't want to share the underlying data but want to provide enough information to support reporting requirements. Public health, taxation, etc. come to mind.
HyperLedger Fabric docs have an example of a manufacturer, vendor and short term finance provider all on the same network with transactions happening instantaneously. Then when you look into case studies, Honeywell has an airplane parts marketplace that’s apparently streamlined their sales process. I’ve seen some Upwork contractors demoing medical data platforms. I didn’t understand that one as much.
What's the chances that we'll have robotic domestic servants before 2032? With AlphaZero, AlphaFold and sort-of OK machine translation, I think it's 50:50, no?
Such a sad story and so unnecessary. IBM acquired Blekko in 2015 during 'peak Watson' and I was fascinated to peek behind the curtains as it were. What I found was both inspiring and terrifying.
There were so many great people who had tremendous insights into applications of machine learning, neural networks, and generalized knowledge engineering as a service. It reminded me in some ways of PARC in the 80's. And like PARC, this effort was in the service to an institution that fundamentally didn't understand the ideas of ubiquitous networked compute that backed the web, much less the value proposition of this core technology.
While I didn't walk the "hallowed halls of executive row", the ripples and changes that emanated from there told of a company desperate to stay relevant being managed by executives who didn't understand the environment but were desperate to stay employed. And for me, nothing is more sad than seeing a 20 - 30 year veteran of a company, sabotage its future to hold on their current job for one more year.
One of my roles at the various companies where I have worked has been "change agent." Getting the company's head around fundamental change that will keep them from getting in their own way down the road. Critical to any change effort it is essential to help people see their role, and more importantly where they add value, in the post change universe so that they won't fight the change with all their efforts.
IBM was being driven at that time in a very top-down sort of approach. Edicts like "This year you will all adapt an agile methodology." Which on their own make no sense at all to the folks lower down the chain. Sort of like saying "Everyone will only wear white pinstriped suits to work from now on." Everyone then incurs an expense of getting a bunch of new clothes, and they have no idea why they have to do this or how it helps the company. It was fascinating to listen to the responses of senior leaders to the "be agile" command. Almost all of them simply discussed how to take what they were already doing, and report them in a "agile" way, so that they could check the box.
That isn't change leadership, that is simply injecting noise into the system and reducing efficiency.
Now it may sound like I think they were all idiots, but I do not. I recognize the challenge of being a senior leader at a company in an industry that they once led and are now trailing. The board of directors might exhort you "go faster, get better, catch up" with no actionable guidance whatsoever. And the strategies that such companies use to recapture some relevance are not unique, buying the "hot new company" and trying to inject their momentum into your own. But it isn't as simple as making the CEO of "hot startup" an EVP in charge of "doing great things, but using the existing staff." Because the existing staff will push back on all the things the newly minted EVP is trying to change because, in part, they don't see what their role and value will be in the changed company. And if you have no role or value, you get RA'd[1].
A good friend of mine used to call them "Corporate Antibodies" and that was a really good analogy. Whenever change was in the air they would activate and work to shut it down. Which is why I spent quite a bit of time learning ways to introduce changes without triggering the corporate immune system. If you do it well, you get no credit at all for the change it just seems like everyone sort of decided that this was the right direction and changed course.
So it is a sad moment for me to see the wonderful work of the engineers and scientists that brought many amazing technologies to market being treated as a humiliating failure on the part of a former giant in the computer industry.
[1] Different companies use different euphemisms for laying people off, Sun use to call them "Job Relocations", Google called them "Group alignments", and IBM calls them "Resource Actions" (you know just balancing some resources by moving some numbers around on a ledger.)
1) To apply for Watson access you needed to show C-level approval, so our CEO put his name and phone number on the application (trying Watson was somewhat his idea). A few months later, an IBM marketing team called HIS CELL and asked for ME. Imagine how it felt to have the CEO walk up to me, deadpan hand me his personal iphone and say "It's for you."..
2) They told me they'd help me with the support data idea, and every meeting we set up they tried to pitch "what if we put Watson on all of your customer's storefronts, we could add a 'powered by watson' banner on every page, and you give us a cut of GMV?". I pivoted them to our plugin framework and told them to build it themselves.
3) To demo the technology, the first step was to buy a $250k server from IBM. To demo it.
Big LOLs all around, never trust big blue.