Basically, starting around 15 years ago, there's the proliferation of bootcamps teaching fullstack development, because software startups were the new hot thing, and they desperately need generalist engineers that were capable of spinning up web app quickly. Rails was the hot thing those days because of this as well. Hence we saw many new grads or even people who change careers to fullstack development and bootcamps churning out these workers at an incredible pace (regardless of quality) but the job market took it because the job market was desperate for fullstack engineers.

During that time, the best career move you can do was to join the startups movement as fullstack engineers and get some equity as compensation. These equities, if you are lucky, can really be life changing.

Fast forward now, the low hanging CRUD apps (i.e., Facebook, Twitter, Instagram, etc) search space has been exhausted, and even new unicorns (i.e., Uber) don't make that much money, if they do for that matter. Now those companies have become big, they are the winners in this winner take all filed that is the cloud tech software. Now these companies these days have no use for fullstack engineers anymore, but more specialists that do few things albeit on a deeper level.

Today, even the startup equity math has changed a lot. Even with a good equity package, a lot of the search space has been exhausted. So being fullstack engineers these days that join startups don't pay as much anymore. Instead, a better move would be to try to get into one of these companies because their pay just dwarfed any startups or even medium / big size companies.

Just my 2c as someone who is very green (5 yrs) doing software engineering. Happy to hear criticism.

Small companies make it possible, large companies make it economical.

Of course, a lot of that is subjective, as it depends on what you find interesting. I don't personally tend to find large-scale projects very interesting because they tend to be worked on by large teams, rendering most individual roles to something much more narrow. But I do know plenty of devs who get very excited about large-scale projects. Vive la différence!

The value of full stack engineering is also plummeting because the tooling i.e. React has gotten so good that the barrier to entry is very low.

The specialty jobs still exist. Planning is still another pay grade. But the average labor cost goes down and the volume goes up.

There are so many apps that could be written but the profit potential is too low to be worth it.

What useless shit are you going to buy with 'life changing' money exactly that a software developer's salary won't allow?

I still have the childish dream of wanting to change the world. Specifically, I want to be involved in certain kinds of political activism that will likely piss off a number of people, and I want to have enough money that I can support my family without needing to back off if my income source is threatened.

I’m lucky enough to be almost at that point due to startup equity.

But in developing and emerging economies you can make a huge impact.

I feel like anything that isn't addressing these two issues is re-arranging chairs on the Titanic as it's headed for a crash.

There are many groups with power that benefit from keeping people misinformed and unable to rationally determine what is truly in their own self interest, all the way from childhood indoctrination on through to old age.

I’d want to neutralize some of the most egregious uses of such misinformation before simply blaming the people entirely themselves.

But I started my career late. I had three different unrelated degrees (no student debt thankfully, I attended public schools), jumping to different fields in my career. I also need to be ready to support my all-single/divorced-female old family members (aunt, mom, grandma). I also will probably have kids in two years.

So a FAANG salary would be nice.

Now, looking back, it makes sense that the next logical step after PCs was the Internet. But from each era looking forward, it's not as easy to see the next "horizon".

So, if each next "horizon" is hard to see, and the paradigm it subsequently unlocks is also difficult to discern, why should we assume that there is no other horizon for us?

I also don't know if I agree that we are at a "logical endpoint of all of these changes". Is computing truly continuous?

However, I think Ben's main point here is about incumbents, and I agree that it seems it is getting harder and harder to disrupt the Big Four. But I don't know if disruption for those 4 is as important as he thinks: Netflix carved out a $150B business that none of the four cared about by leveraging continuous computing to disrupt cable & content companies. I sure wasn't able to call that back in 2002 when I was getting discs in the mail. I think there are still plenty of industries ripe for that disruption.

The end-goal is being able to talk to anyone at any time, remember anything you've seen before, and know the answer to any question you can phrase that someone has already answered.

(Now, you might say that parts of it sound less than ideal, but I think we'll get there by gradient descent, though may be with some legal or counter-cultural hiccups.)

Sure, and the iphone was the same thing - I had a 3G windows phone years before the iphone that essentially did all the same things. But the iphone was still a breakthrough nonetheless.

It’s hard to see how the incumbents could be beaten — precisely because how effective they are around data, buying potential competitors (Instagram, YouTube) .... but this is precisely because we don’t know what/if the next market shift is.

What happens if AI takes off? What happens if 3D printing magically becomes 100x more efficient and you can print anything you want from home?

We don’t know. It doesn’t seem like the big incumbents could be defeated, but history repeats itself.

Microsoft, IBM, Oracle... What is the other one?

Or, right, wrong decade.

(My point is, it completely not obvious if it is getting harder to disrupt the incumbents.)

That, I think is where the metaphor Ben uses breaks down. The automobile is a single idea (move people around with an ICE). Tech is more like the ICE than the car. So, there might not be much disruption to consumer hardware (Apple) companies, or search (Google) companies, or cloud computing (Amazon, Microsoft) companies. But there will still be lots of disruption to come as tech (just like the ICE) gets applied to new features.

Cisco, of course.

So, I see this article as being a part of that thread. The conclusion is that the Big Four are not going to get disrupted, which is bad, and drawing some conclusions we need a new framework of antitrust to allow for it. I might be putting words in his mouth, but I don't think it is really that much of a jump if you read his body of work, especially recently.

Up until the web existed, I think it was extremely hard to usefully predict the Internet's impact. TCP was invented in 1974, but it wasn't until 1993 that we started seeing things that really pointed to where we were going: https://en.wikipedia.org/wiki/List_of_websites_founded_befor...

Of course, everybody knew computers would be important. But that was true starting in the 1960s. E.g., Stand on Zanzibar has a supercomputer as a central plot element.

Some people like me still lament the loss of the 90s internet in some ways, as it felt like a more "wild west" domain and not saturated and stale like it is today.

https://en.wikipedia.org/wiki/Information_superhighway#Earli...

The Brotherton reference in particular interests me -- masers and light-masers (as lasers were initially called) were pretty brand-spanking new, and were themselves the original "solution in search of a problem". I've since come to realise that any time you can create either a channel or medium with a very high level of uniformity and the capacity to be modulated in some way, as well as to be either transmitted/received (channel) or written/read (medium), you've got the fundamental prerequisites for an informational system based on either signal transmission (for channels) or storage (for media).

Which Brotherton beat me to the punch by at least 55 years, if I'm doing my maths correctly.

I've made a quick search for the book -- it's not on LibGen (though Internet Archive has a copy for lending, unfortunately the reading experience there is ... poor), and no library within reasonable bounds seems to have a copy. Looks like it might be interesting reading however.

Point being: Brotherton (or a source of his) had the awareness to make that connection, and to see the potential as comparable to the other contemporary revolution in network technology, the ground-transit superhighway. That strikes me as a significant insight.

Whether or not he was aware of simultaneous developments in other areas such as packet switching (also 1964, see: https://www.rand.org/about/history/baran.html) would be very interesting to know.

Not much information on him, but Manfred Brotherton retired from Bell Labs in 1964, and died in 1981:

https://www.nytimes.com/1981/01/25/obituaries/manfred-brothe...

Brotherton wrote a book on Masers and Lasers in 1964, you might find more info in that: https://www.amazon.com/Masers-Lasers-They-Work-What/dp/B0000...

is that the one you mean?

Baran's full set of monographs written for RAND are now freely available online. I'd asked a couple of years ago if they might include one specifically, and they published the whole lot. Asking nicely works, sometimes.

Yes, there's interesting material there.

https://www.rand.org/pubs/authors/b/baran_paul.html

Definitely, you see new industries replacing old ones. Acknowledging the above isn't denying progress. But every industry consolidates down to a few large companies.

But this doesn't fit any of the upcoming trends. The biggest current trend is edge computing where cloud-based services introduce issues around latency, reliability and privacy. These are big money problems - see smart speakers and self-driving cars. The cloud players are aware of this trend - see AWS Outposts that brings the cloud to the needed location and AWS Wavelength where they partnered with Verizon to bring compute closer to people.

But privacy in a world full of data-driven technology is still very much an unsolved problem. And most of the major technology players have public trust issues of one sort or another that present openings for competitors in a world where trust is increasingly important.

Similarly, I bet that our great-grandchildren will look upon the Internet, e-commerce, and mobile phones the same way we look upon railroads, paddle steamers, and power looms. Great inventions for their time, and drivers of huge fortunes, but also quaint anachronisms that have long since been replaced by better alternatives.

Notice that the article focuses almost entirely on I/O and the physical location of computation. This is a pretty good sign that we're still in the infrastructure phase of the information revolution. When we get to the deployment phase, the focus will be on applications, and our definition of an industry focuses on what you can do with the technology (like fly or drive) rather than how the technology works. In between there's usually an epochal war that remakes the structure of society itself using the new technologies.

FWIW, there was a similar "quiet period" between the First and Second Industrial Revolutions, from 1840-1870s. It was very similar: the primary markets of the original industrial revolution (textiles, railroads, steamboats) matured, and new markets like telegraphs were not big enough to sustain significant economic growth. But economic growth picked up dramatically once a.) the tools of the industrial revolution could be applied to speed up science itself and b.) the social consequences of the industrial revolution remade individual states into much larger nation-states, which created larger markets. That's when we got steel, petroleum, electrification, automobiles, airplanes, radio, and so on.

Competition is important, but to drive efficiency - weed out bad ideas and bring down costs of already created innovations. But the thing that usually drives monoliths out of business is... new monoliths.

The somewhat contrarian takeaway is that some (keyword) amount of consolidation is good.

The truth is somewhere in the middle: definitely, you see some large companies invest heavily but (more commonly) you see small firms nibble at the edges of an existing product until it is too late for the larger companies.

Saying that monopoly produces innovation is like saying government produces innovation. It happens but given a long enough period all things happen. The question is about incentives: the incentives to innovate within large companies are terrible, that is why it doesn't happen most of the time.

Also, consolidation has happened in all industries at all times. It is a function of things that repeat: knowledge curves, lindy effects, etc.

Just generally: be wary of Thiel and his ilk. They have a predilection for ahistorical nonsense. The history in this area, broadly business history, is particularly difficult and not well known (the only tech person who I have seen get close is Patrick Collison..and then...not really).

However monopolies are not always due to innovation, nor our monopolies inefficient. As you mentioned, it's a function of things that repeat, but also due to stronger players that gobble up less efficient and/or innovative firms.

I would read between the lines. Business history is indeed difficult.

First, I replied to a comment. The majority of your points should be directed there. Second, your point about monopolies or why they happen is just uninteresting (the question of "always" is not something that can be answered). Third, your point about the most innovative companies tending to become monopolies is wrong...I am not sure how little you have to know to think this but it is certainly very minimal. The historical evidence is that industries consolidate down to a few large companies, not that they become monopolies. Fourth, again, I repeat what I said about ahistorical nonsense. Neither in theory or reality is monopoly a natural consequence of capitalism. Fifth, most monopolies that have existed in reality, by number, are not privately-owned, they are not innovative. There is a fairly obvious inverse correlation between monopoly and innovation (again though, the issue that is confusing you is thinking that innovation -> monopoly...this isn't a thing).

I don’t see how a company that’s in a life or death struggle could pour hundreds of millions/billions of dollars into R&D but perhaps I’m missing something

Sure, that's what happened.

But what jumps out for me is that, at both ends of that range, users are relying on remote stuff for processing and data storage. Whether it's mainframe terminals or smartphones, you're still using basically a dumb terminal.

In the middle, there were personal computers. As in under our control. That's often not the case now. People's accounts get nuked, and they lose years of work. And there's typically no recourse.

As I see it, the next step is P2P.

Of course, there are debates around which inventions count as significant. And there is recency bias.

Never underestimate the power in something easy to communicate.

Yes, I suppose that's the biggest thing with these "futurologists": their predictions are both tantalizing and easy to digest. I reserve the right to remain skeptical about any of these Silicon Valley religions though.

What strikes me as particularly interesting about Silicon Valley and some techie circles -- as opposed to Nostradamus -- is that many of these people self-identify as hiperrational, agnostic, atheist or wary of traditional religions, yet here they are, building their own religions under a more palatable technological guise (I could list ideas like the Singularity, Super AI good or bad, immortality, "we're living in a simulation", "every problem in the world can be fixed with the right app", etc, but if the list of absurdities goes long enough I'm sure to hit some raw nerve, so I'll stop here).

These modern day Nostradamuses also tend to overinflate their own importance in the wider world. Outside of techie circles Kurzweil is a nobody, and the notion that his theories are some bar that other theories must somehow pass is laughable.

He claims he's right even when he's obviously wrong. He is not someone whose predictions should be blindly trusted.

Likewise, if someone said "human aging and death are unavoidable" this wouldn't be bold just because Kurzweil has written a lot about immortality.

A lot of work is being done to make bio-silicon fusion real, with use cases like creating olfactory sensors.

And our increasing control over both brain and genes may be the pathway to more general biological computation.

https://www.ucsf.edu/magazine/control-brains-genes

It seems like the whole analysis is predicated on the idea that technology = software made in Silicon Valley, with unimportant secondary factors. That 3M and ExxonMobil are not "tech" companies because they don't make iPhone apps.

Every company is a tech company, not because we've had computers for a while, but because technology is what we build to get what we want.

These kinds of narrow, myopic, siloed takes miss the forest for the trees.

If you think the epitome of human evolution is going to be people looking at bright rectangles for eternity, you haven't been paying attention to what technologists are doing.

Also, giants are giants. In manufacturing, there are absolutely vast advantages to economy of scale. In tech, except for network effects, it's very easy for a very broad array of upstart companies to dominate their respective arenas at the 100bn level.

> today’s cloud and mobile companies — Amazon, Microsoft, Apple, and Google — may very well be the GM, Ford, and Chrysler of the 21st century.

Well, except google is not a cloud or mobile company. They are an advertising company.

I don't agree with this at all. This is like saying "the internet is a natural extensions of the operating system, therefore Microsoft Windows will remain all powerful and the sole route to consumers"

Bill Gates in his famous memo realised that this wasn't the case, and Google realized that mobile did to the internet what the internet did to Windows (hence Android).

Wearables are radically different to phones. People want to use them differently, and interact with them in different way to how they do with phones.

To be clear: We are in the very early days of wearables, and Apple is far and away the dominant player (and maybe Garmin). But there is huge disruptive potential here.

I believe at least one more revolution would still be possible before we have a long period of evolution. It will be a shift from centralization to de-centralization (one more time), actually to federation. De-centralized federated systems might be able to get social networking and payments to the level where it finally works well and only needs to be gradually improved.

By definition, doesn't it always seem like this?

Jim Barksdale (Netscape) said there are 2 ways to make money - bundling and unbundling. What can be unbundled from the incumbent bundles, in order to be offered in a more fit-for-purpose way, or with a better experience?

How might that answer change if the world's political structure changes? How might that answer change if processing, storage and networking continue their march towards ubiquitous availability?

That's possible, but I see things that lead to me think that we're not there.

Primarily, there are a number of rather serious problems with the cloud, some of which are inherent to the paradigm and likely can't be resolved -- we'll just have to live with them.

When a paradigm has such problems, the possibility always exists that a new way of doing things can come about that sidesteps those problems.

In a similar vein, Apple, Google and Microsoft control the medium and have grown so powerful, I can't imagine there ever being a new "Google" that comes about the old grass roots method.

Someday Apple will be bought though, probably by Facebook.

The rest doesn't really seem to have enough evidence for such a bold claim.

There is

> IBM’s mainframe monopoly was suddenly challenged by minicomputers from companies like DEC, Data General, Wang Laboratories, Apollo Computer, and Prime Computers.

So, to shed some more light on this statement, especially about "mainframe monopoly", let me recount some of my history with IBM mainframes:

(1) Uh, to help work myself and my wife through grad school, I had a part time job in applied math and computing: Our IBM Mainframe TSO (time-sharing option) bill was about $80,000 a year, so we got a Prime, and soon with my other work I was the system administrator. Soon I graduated and was a new B-school prof where the school wanted more in computing. So, I led an effort to get a Prime -- we did. IBM and their super-salesman Buck Rodgers tried hard but lost.

The Prime was easy to run, very useful, and popular but would not have replaced IBM mainframe work running CICS, IMS, DB2, etc. Of course, in a B-school, we wanted to run word processing, D. Knuth's TeX math word whacking, SPSS statistics, some advanced spreadsheet software (with linear programming optimization), etc. and not CICS, IMS, DB2.

(2) Later I was at IBM's Watson lab in an AI group. For our general purpose use, our lab had six IBM mainframes, IIRC U, V, W, X, Y, Z. As I recall they had one processor core each with a processor clock likely no faster that 153 MHz.

Okay, in comparison, the processor in my first server in my startup is an AMD FX-8350 with 8 cores and a standard clock speed of 4.0 GHz.

So, let's take a ratio:

(8 * 4.0 * 109)/(6 * 153 * 106) = 34.9

so that, first cut, just on processor clock ticks, the one AMD processor is 35 times faster than all the general purpose mainframes at IBM's Watson lab when I was there.

But, still, on IBM's "mainframe monopoly", if what you want is really an IBM mainframe, e.g., to run old software, then about the only place to get one is from IBM. So, IBM still has their "mainframe monopoly".

Or to be extreme, an Apple iPhone, no matter how fast it is, does not really threaten the IBM "mainframe monopoly".

Continuing:

> ... like DEC, Data General, Wang Laboratories, Apollo Computer, and Prime Computers. And then, scarcely a decade later, minicomputers were disrupted by personal computers from companies like MITS, Apple, Commodore, and Tandy.

Not really: The DEC, DG, ..., Prime computers were super-mini computers and were not "disrupted" by the PCs of "MITS, Apple, Commodore, and Tandy."

The super-mini computers did lose out but later and to Intel 386, etc. chips with Windows NT or Linux.

> ... Microsoft the most powerful company in the industry for two decades.

Hmm. So now Microsoft is not so "powerful"? Let's see: Google makes it easy to get data on market capitalization:

Apple: $1,308.15 B

Microsoft: $1,202.15 B

Alphabet: $960.96 B

Amazon: $945.42 B

Facebook: $607.59 B

Exxon-Mobil: $297.40 B

Intel: $256.35 B

Cisco: $201.47 B

Oracle: $173.73

IBM: $118.84 B

GM: $50.22 B

Microsoft is still a very powerful company.

Uh, I'm no expert on Apple, but it appears that the Apple products need a lot of access to servers, and so far they tend to run on processors from Intel and AMD with operating system software from Microsoft or Linux -- that is, Apple is just on the client and not the server side.

It appears, then, that in computing Microsoft is the second most powerful company and is the most powerful on the server side.

Sure, maybe some low power ARM chips with 3 nm line widths and Linux software will dominate the server side, but that is in the future?

And personally, I can't do my work with a handheld device, need a desktop, and am using AMD and Microsoft and nothing from Apple. A Macbook might suffice for my work but seems to cost maybe $10,000 to have the power I plugged together in a mid-tower case for less than $2000.

Broadly it appears that the OP is too eager to conclude that the older companies are being disrupted, are shrinking and are fading, are being replaced, etc.

Maybe the main point is just that in the US hamburgers were really popular and then along came pizza. So, pizza is popular, but so are hamburgers!

I also go along with the point of zozbot234 at

https://news.ycombinator.com/item?id=21986141

> Software is still eating the world, and there will be plenty to eat for a long time.

The difference between a car company and a software company is economy of scale. I.e. economy of scale dominate the physical world but does not exist in the software world since I can replicate software at zero cost.

In addition, new tools and new processes for software has increased the productivity times fold, which means that you need fewer developers for new software.

I predict two shifts in the tech world:

1) Move to the edge. Specially for AI, there is really no need for a central public cloud due to latency, privacy, and dedicated hardware chips. I.e. most of AI traffic is inference traffic which should be done on the edge.

2) Kubernetes operators for replacing cloud services. The value add of the public cloud is managing complexity.

You don't hear him talk about economies of scale because marginal costs are negligible for software companies. Besides, network effects and vertical integration are sufficiently powerful to control the market.

> In addition, new tools and new processes for software has increased the productivity times fold, which means that you need fewer developers for new software.

There are other barriers to entry besides the cost of writing software, like product, sales, operations, and most importantly, network.

The case for big tech today is still the economy of scale and not network effects (maybe facebook have those, but it exists only if the interface to facebook does not change).

The big tech players have economy of scale, due to their ability to use automation and offload the risk of managing complexity (I.e. one AWS engineer can manager 1000's of machines with AWS software).

No wonder, that the software that manages the public cloud is still closed source.

However, with Kubernetes operators, there is a way to move those capabilities into any Kubernetes cluser.

> The case for big tech today is still the economy of scale and not network effects (maybe facebook have those, but it exists only if the interface to facebook does not change).

This is only true if you believe that the greatest cost of developing software is running hardware. The greatest cost of developing software is developing software. Not only are economies of scale in compute management negligible except at massive scale, the cost of compute has declined dramatically as the companies you've described have made their datacenters available for rent through the cloud. Yet the tech giants persist.

Facebook, Google, Netflix, Amazon all have considerable network effects that you're not considering. For each of these companies, having so many customers provides benefits that accrue without diminishing returns, giving them a firm hold on market share. See https://stratechery.com/2015/aggregation-theory/

Ben is saying that the only way to topple the giants is by working around them and leveraging new computing technologies better than them. He makes the (admittedly speculative) case that this is no longer possible because we can't bring compute any closer to the user than the mobile devices.

> However, with Kubernetes operators, there is a way to move those capabilities into any Kubernetes cluser.

Kubernetes, at the scale of technologies we're discussing, is a minor optimization. Introducing k8s costs more than it helps far until far into a company's infra maturity. Even if most companies deployed k8s in a manner that significantly reduced costs, it's not enough to overcome the massive advantages existing tech companies have accrued. Not to mention all of the big tech companies have internal cluster managers of their own.

See: Walmart -> Amazon, Nokia->Apple, MSFT -> Andriod.

I mean, what more of network effect did MSFT had in the 90's. It was dominating both the OS layer AND the app layer (office). And yet, it does not have ANY share in mobile.

Kubernetes is not minor optimization if you think about what it is. Yes, if you see it as mere container orchestration. But it is the first time that a widely deployed, permissionless, open API platform exists.

this is based on a very dubious assumption that bringing compute closer is the only path for innovation.

and even that is not true, you could imagine compute being even closer with a direct brain interface (actually you could consider google glasses to be an attempt at bringing compute closer)

Network effects are THE factor in software because the marginal cost tends towards zero with each incremental user in the network. The edge adds cost per node.

Up until the point that users are paid to connect to the network and/or the network is directly linked to the user with the I/O line completely obviated, the economics of hardware and management underlying the network will tend towards economies of scale... which is the point Ben is trying to make.

Inferencing is done at the edge, but training must be done centrally.

Anyone else is busy building little dumb cubes with microphones and speakers that send sound bites into clouds and receive sound bites to play back (heck, even Apple does it this way with Siri). Or other dumb cubes that get plugged into a wall socket and that can switch lights that you plug into them by receiving commands from a cloud (even if the origin of the command is in the same room). Or dumb bulbs that get RGB values from a cloud server which inferred somehow that the owner must have come home recently and which then set the brightness of their RGB LEDs accordingly. Or software that lets you record sounds bites, send them into the cloud and receive transcripts back. Or software that sends all your photos to a cloud library where it is scanned and tagged so you can search for "bikes" or whatever in your photos.

No matter what you look at in all that stuff that makes up what consumers currently consider to be "AI", it does inference (if it even does anything like that at all) on some cloud server. I don't like that development myself, but unfortunately that's how it is.

But then a lot of edge cases don't make a lot of sense. The best edge use cases are fan-in (aggregation and data reduction), fan-out (replication and amplification - broadcasting, conferencing, video streaming, etc.) and caching (which is just a variant of fan-out).

The rest of the cases are IMHO largely fictional - magical latency improvements talked about in the same context as applications that are grossly un-optimized in every way imaginable, AR/VR, etc. Especially the AR/VR thing.

Beyond that the only thing left is cost arbitrage - selling bandwidth (mostly) cheaper than AWS.

What's the use case for moving inference to the edge? Most of the inference will in fact be at the edge - in the device, which has plenty of capacity - but that's not the case you're describing.

For inference, I See 90% on the edge (I.e. outside of the clouds).