> Nowadays people get told that if they think they’ve figured out something about gravity, they’re probably a crackpot. Instead, they should wait for very large government-funded programs full of well-credentialled people to make incremental advances.
Maybe we approach limit of human cognitive abilities and another Newton is not possible for current problems? Maybe to find a cure for cancer you need to spend 10k hours studying biology, 10k studying chemistry, 10k studying machine learning and then spend 100k hours on the problem, which it's not possible for a human being.
Possibly. But then, we've always been good in solving problems with tools. Could we reduce the necessary "10k" learning by building better tools for accessing knowledge?
Right now, scientific papers are a shitshow, and even refined and systematized knowledge in textbooks isn't as accessible as it could be in the digital age. Could we encode knowledge in more powerful tools allowing us to explore through free-form simulations?
The goal here would be to make discovery of promising solutions more time- and effort-efficient.
Related, I feel we need to figure out a way to systematize information in scientific papers to make mining them for cross-cutting insights possible. I suspect there are lots of discoveries hiding in plain sight, if one knew which particular papers from which disciplines touch on the same underlying phenomenon or concept.
Related, I feel we need to figure out a way to systematize information in scientific papers to make mining them for cross-cutting insights possible. I suspect there are lots of discoveries hiding in plain sight, if one knew which particular papers from which disciplines touch on the same underlying phenomenon or concept.
This is interesting problem, unfortunately it's really, really hard.
I'm most familiar with mathematics, so I'll use it as an example, but this is not limited to mathematics.
If you take any new paper on research mathematics, in a hot field like algebraic geometry or partial differential equations, then unless you're an expert in that field, it will almost always be literally impossible for you to understand -- not simply hard to follow the arguments, but simply impossible to understand even what it's about. Look, I just grabbed random example from recent posts on arXiv[1]: try reading an abstract and explaining it back to me. For 99.99% English speakers, this will be indistinguishable from random gibberish in a paper written by recurrent neural network trained on arXiv papers.
However, 0.01% of people will understand something, and for probably 1% of these, the abstract will make perfect sense. However, if you ask these people to explain it, you'll either spend an hour or two on getting some very superficial understanding of what's at stake here, which won't be very useful to you -- you still won't be able to actually read and follow the paper, and use the insights for your own purposes. Alternatively, and if you're intelligent enough, they can spend a year or two teaching you required background. Then you can see the insight for yourself.
The problem here is that you need literally years of background studies to appreciate the insight. There likely is no quick and easy way around it, otherwise some of the extremely smart people involved would already have had figured it out -- assuming otherwise is hubris. This doesn't mean that the system cannot be improved upon: there's tons of ways to make things simpler, clearer, more digestible. However, you'll still be left with hard problems of hard things being hard.
OK, let's check your numbers. There are about 1.5 billion people who speak English, and you are telling us that only .0001 * 1.5 billion = 150,000 of them will get anything out of the abstract? And that only .01 * 150,000 = 1,500 of those will find it to make perfect sense? That doesn't seem right.
Abstract. Using elliptically fibered Kummer surfaces of Picard rank 17, we construct an explicit model for a three-parameter bielliptic plane genus-three curve whose associated Prym variety is two-isogenous to the Jacobian variety of the general three-parameter hyperelliptic genus-two curve in Rosenhain normal form. Our model provides explicit expressions for all coefficients in terms of modular forms.
Oh. Oh my. Checks list of Sokal Squared spoof papers, nope. "Indistinguishable from random gibberish in a paper written by a recurrent neural network" it is then. Rather than being conservative, now I see that you were wildly optimistic in your estimate. There can't possibly be over 1,000 people in the world to whom this would make perfect sense, can there?
IMO it can be both "hard" and "really, really hard", depending on paper's difficulty. Some papers are much easier to read - e.g. those describing experimental results. Often, being the 0.01% who understand something is enough - it's one thing to read a paper, understand the basic reasoning and trust the conclusion / proposed method; it's another and more difficult thing to fully comprehend the paper and verify its correctness. Often you don't need that full comprehension to make progress and put the paper to good use.
> The problem here is that you need literally years of background studies to appreciate the insight. There likely is no quick and easy way around it, otherwise some of the extremely smart people involved would already have had figured it out -- assuming otherwise is hubris.
That's fair; something of a scientific version of efficient market hypothesis, I guess. If following the bleeding edge of a scientific domain didn't require years of background studies, it would be easy, so scientists would quickly zoom through it, until the going got difficult again.
> This doesn't mean that the system cannot be improved upon: there's tons of ways to make things simpler, clearer, more digestible. However, you'll still be left with hard problems of hard things being hard.
Yeah, I was just thinking about ways to tackle the things that can be made "simpler, cleaner, more digestible". I don't deny that there are fundamentally hard problems we have to face directly, but right now, those problems are wrapped in a lot of irrelevant cruft that makes them bigger than they really are.
> try reading an abstract and explaining it back to me
Challenge accepted, though I know the result kind of reinforces your point. But here's what I understood from that abstract:
> Using elliptically fibered Kummer surfaces of Picard rank 17, we construct an explicit model for a three-parameter bielliptic plane genus-three curve whose associated Prym variety is two-isogenous to the Jacobian variety of the general three-parameter hyperelliptic genus-two curve in Rosenhain normal form. Our model provides explicit expressions for all coefficients in terms of modular forms
We took a particular weird abstract shape with interesting properties, and used it to describe a particular different weird abstract shape, whose properties are important to us. Abstract shapes can be written down as maths, and depending on the way you write it, they can have properties exposed directly as "knobs" to tweak - e.g. "circle of radius r" has a radius exposed directly, whereas "circle that fits in that place" hasn't. In this paper, our description of the weird abstract shape has its important knobs exposed.
Depends what you mean by AI... yea if you ask Siri for a cure and she succeeds then you're the instrument, but if I make clever use of the statistics and math behind it all, and find a way to apply it to some drug discovery or procedure, then I'm the hero, and the AI was just a tool.
If you hop into an excavator, you can't really compare yourself with great builders of the past, but you can move ground around much faster than they ever could. This is what I had in mind - not building oracles for scientific discovery (though that would be cool, too), but building excavators for the mind, and airplanes for the mind (and building a Bagger 288 for scientific papers).
I realise that your numbers are only meant to be illustrative, but it's worth realising that this is "only" 65 hours a week for 40 years. A lot? Yes. More then I'd be willing to work at a typical desk job[1]? Probably. But feasible for a passion project? Definitely! (and doesn't even necessarily require starting before you hit 25, although that clearly helps...). The limiting factor is not so much that nobody can do this, but that (short of independent wealth, which I think can bring its own set of constraints and expectations) very few people ever get the opportunity to do this without a lot of interruptions. I don't think it's impossible to imagine a society where that isn't true.
[1] although... "thinking" can stack surprisingly well with some activities we'd consider leisure, like walking or (at least in my case) gardening. So maybe this isn't really going to be 65hrs/week at a desk...
Pretty much -- for example, I had definitely spent 10k hours each studying biology, chemistry and computer science by the time I reached age 21.
But, all this thinking is in my experience pretty useless in terms of real world results (and I don't mean results like Stanford idolizing you). You're not going to "think" your way into curing cancer no matter how many hours of biology or chemistry you take, and I should know, because I've seen people try. It's pretty hard to "think" up a company the size of Amazon, too, especially in a world where a lot of industry have their Amazon. You need capital and a degree of self-confidence bordering on manic delusion and when you have this you still need to not do what Elizabeth Holmes did and know when you've failed and give up what may have been ten or twenty years or a lifetime and start something else.
It's not the 100k hours. It's the very large odds they will have been for nothing, and picking up whatever is left of your life after.
It's not the 100k hours. It's the very large odds they will have been for nothing, and picking up whatever is left of your life after.
That's an interesting take. But my experience is that there is a non-negligible set of people who would see a lifetime spent working on their chosen problem to be well-spent, even if they don't eventually succeed.
No, we build off of each other’s knowledge. We learn some things, simplify them, and then build on that knowledge. We didn’t go right from wires and signals to JavaScript and web browsers, it was incremental, where each generation built off of the last one’s work.
That’s how many hours it would take today. But if we get a few fancy new libraries for ML, it could be trivial to implement. 20 years ago, if I told you a single developer could deploy a website with a db + authentication in about 20 mins, you’d call me a liar. But today, you can use a fullstack generator and deploy to heroku with the press of a few buttons.
> You can still visit the Bay Model in that Sausalito warehouse, but today it’s just a tourist attraction: big plans for the future have become archaic curiosities.
The Bay Model is well worth visiting. While the Reber Plan to dam up the bay would have been an environmental disaster, the model is really cool. It was actually used for many years after the plan was abandoned. It was only the rise of fluid dynamics simulators that made it obsolete.
"Zero To One might be the first best-selling business book based on a Tumblr. Stanford student Blake Masters took Peter Thiel’s class on startups. He posted his notes on Tumblr after each lecture. They became a minor sensation. Thiel asked if he wanted to make them into a book together. He did."
The Amazon example is interesting. Amazon gained a monopoly on books in the US and exploited that to become a monopoly in everything. Meanwhile in 1980s Germany you could order books through your local bookseller of choice who would go through one of two wholesellers who had most books in stock for next-day delivery. But neither Libri nor KNV chose to exploit their position to become Amazon before Amazon. That, or time wasn't yet ready.
And a US-specific aspect of your second item: the weird way US sales tax is set up meant that Amazon didn’t have to pay any for a long time, giving it an automatic ~5% price advantage in most states.
Amazon was pretty clearly trying to drastically expand its markets early on and should have been a warning bell to incumbents in other industries. For example, they bought local Seattle area Egghead Software and used that as a beachhead into the supply chain for retail boxed software. They bought all kinds of stores going out of business. For a while, you could even see other brands sell their stuff using Amazon as their main portal. Target did similar buying Mervyns for access to certain brands that it didn’t have for so long. Funny enough, Target used to use Amazon as it’s e-commerce storefront.
2, Price competition likely was less important; in Austria (and I think, Germany) there exists the "Buchpreisbindung", the price of books is mandated, no seller must offer a lower price; also, tax was always included, from day one.
They still won big, very early, very fast. I remember that an employee of a (now defunct) bookstore told me "please order via Amazon, you'll get the book faster, and I cannot offer any added value".
Zero to One is my favorite "startup" book, Thiel has a lot of interesting insights and I wish he was a bit more public with his thoughts. Trying to search for Thiel talks online that don't take place during his book tour has been tough for me.
I'm actually glad he isn't going on a self-congratulatory speaking tour, gives me the impression he does indeed have important things to think about and work on.
This might be an unpopular opinion, but the Amazon example is bad. Bezos didn't get "richer than God" by making a bookstore -- this is just grossly misleading. AWS and Prime (both criticized upon release; Prime lost money for years) are the two main reasons Amazon took over the world. Amazon is a master class in pivoting and trial and error. Sometimes it loses (Fire Phone), but when it wins, it wins big.
also Thiel (at least as represented in the review here) seems to systemically understate the role of luck and environment.
One contribution to Amazon's success was also the great culling of (potential) competitors after the dotcom burst. They were really lucky to rake in a 700 million investment barely a month before the crash, and most competitors afterwards had a hard time raising serious money.
Now sure you can argue that there's strategies you can pick that maximise your chances of abusing these crashes, but they're very hard to predict and if they don't come you might lose out, and I don't think Bezos ever anticipated the dotcom bubble.
So chance and timing really play a gigantic role in creating successful businesses, there are not always secrets or geniuses behind successful enterprise.
Just as "make a bookstore" isn't the key to success, I don't believe you can say "pivot a lot" or "trial and error" is the key to success either. Plenty of startups pivot and run out of runway.
My current thinking is that a big piece of success is taking risks and being able to absorb the losses.
Generally big payouts don't come from a sure thing; you have to take multiple risks that could potentially have big payouts and survive long enough for one or more of them to pan-out.
True, this is a good point. The key to startup success is probably the same as the key to winning at Poker: win more than you lose :) Although I guess my point was just that I don't think Bezos thought that being a book salesman would make him a billionaire (as the article implies).
Ruthlessly identify and pursue existing capabilities that are profitable or that capitalize on or provide unique or rare market capabilities (which you can later try to turn into profitable areas), and always been experimenting to find more.
Right time and place, luck, skill and money in varying relative quantities. People focus on the skills, not unimportant by all means, but it is not the secret sauce.
as a graduate student in CS (ML and theory) all these comments about people not believing in their own ability to invent things via their own reasoning runs 100% opposite to my own experience. weird. maybe i've just found a good local optimum in my life choices and starting place (birth/white privilege etc).
He's a California based psychiatrist who also happens to write rational fiction (reddit.com/r/rational) and has interesting blog posts. I don't think he has any special qualifications or status that would make his review any more authoritative than anyone else's, but I really enjoy his writing style.
He is a pseudonymous blogger who has been described as one of the most influential bloggers by more than a few other very influential bloggers.
If you wish to know more, I'd nominate "Who by very slow decay" [1] as his one work that everyone should read, because more people knowing it would make the world a better place. (edit: content warning: hospitals and death. It's not a pleasant read, but I think it's a necessary one.)
It wasn't always like this. There has been a steady rightwards drift these past years and now it has become much further to the right than both Scott and the majority of the blog's audience.
It was a containment thread to keep certain discussions from taking over the rest of the board. It was pinned so it would be more effective at doing that. However, it then stole most of the board's activity and/or attracted its own set of users.
I like /r/slatestarcodex, and I like the culture war thread.
But it's worth emphasizing Scott doesn't participate in that thread, and he doesn't necessarily like it either. In fact, from what I can tell he's not a huge fan of lots of the conversations that go on there, and the topics discussed.
If anyone were to judge him on comments, please only do it based on the curated comments on his website, where he deletes and bans people who are uncivil.
Ahh, ok. I recently came across his blog and the subreddit, and based on the huge activity in that thread I figured that was a prominent creation of his. Thanks for the clarification.
As I'm sure everyone has noticed, the culture war thread has essentially grown to devour all of /r/SlateStarCodex. Also, we talk about really weird stuff here. That's intended, and it's something I like about this community; however, given the weirdness, Scott Alexander no longer wants it on /r/SlateStarCodex. We're moving this thread to another subreddit, and after some internal discussion, we've realized that only a subset of our moderators want to be responsible for the new culture-war-specific subreddit.
So, basically an attempt at image clean-up. His audience created a regular discussion based on the terminology of his original content, but he's trying to become more popular to a broader audience. If people new to him were to search, he'd be able to put some distance, should this separation be effective. That's the gist of what I'm getting from reading the latest discussion.
But politics exists, much real stuff happens there, and also, it's great entertainment. It's also great training, if you don't succumb to bad thinking. It's better doing in company of people who try to be civil and use logic, even if it usually barely works.
Resolving this tension is part of Scott's writing from very early on. This is not just image clean-up, it's dealing with a difficult situation.
but he's trying to become more popular to a broader audience
Not so much that, but to avoid repercussions in his real life. There are topics being discussed that are real sacred cows, and even if his conclusions are "correct", sometimes one is considered evil just for daring to question the conventional values. (indeed, that's much of what the "culture war" thread is about)
Since his writing is just a hobby, he doesn't want fallout from that to impact his real professional career.
Yeah, understood. Personally, I commend him. I sure as hell wouldn't put my name to controversial topics (even if said discussion itself should, ideally, NOT be controversial). In today's social climate that takes some serious courage, and it's not really worth it unless you can be employed regardless of opinion. I'm guessing in his sphere that's not permitted, which is unsettling.
A more parsimonious explanation would be the comment section of any public forum on the internet quickly becomes a shit hole, and when that shit hole is in your name, but you don't participate, that's not a fun position to be in.
Maybe we approach limit of human cognitive abilities and another Newton is not possible for current problems? Maybe to find a cure for cancer you need to spend 10k hours studying biology, 10k studying chemistry, 10k studying machine learning and then spend 100k hours on the problem, which it's not possible for a human being.