I find the authors point not very compelling.. Bill Gates was by all accounts an exceptional programmer at one point and then spent a long time evaluating software engineers. He seems like a natural person to gauge AI progress in coding?
Around when AI was getting much better at SQL I was writing SQL everyday at work and had been for years. I don’t think it would’ve been hubris for me to judge that it was getting really good and would shortly be super human at SQL. It would’ve been correct anyway.
He also tries to dunk on Gates by saying he claimed he produced novel problems in science to test AI.
I don’t think the author realizes that “AP” is an exam for American high schoolers. Gates is only claiming he made new test questions at a high school+ level that wouldn’t have been in the training set for AI. I don’t see how it’s so unbelievable he could do that.
> Gates is only claiming he made new test questions at a high school+ level that wouldn’t have been in the training set for AI. I don’t see how it’s so unbelievable he could do that.
It’s unbelievable because Gates is neither a biology exam author nor a biology textbook author, so how would he even know what’s in the training set for AI? To know, you would need to be an experienced biology teacher and survey the pedagogical literature.
If you did well on AP Bio in the distant past and have kept up with the field of biology like Gates it is normal you could ask some high school exam level questions.
When I was studying for AP Calculus or Literature etc I’m sure I could’ve made decent sample questions.
Nobody is disputing whether Gates could come up with some exam questions. They're disputing whether Gates could come up with novel exam questions that weren't in the AI training data.
Maybe he was into biology for a hobby. Would fit his character, much like half of HNers are probably near-experts in some random field they haven't had formal training in. It's not unusual.
And would fit the fact that he funded biotech R&D too.
This is the crux though, isn't it? Are people as overconfident as the article claims, or are there many 'hobbyist' experts milling around? I did a Bachelor's in philosophy before switching to CS, and have been fascinated by IR/political theory since high school. While I could not hope to learn it all, I can hold a good conversation with a researcher in either philosophy or IR, especially if it intersects with a topic of my core expertise.
To flip it around, I have friends who I would consider (hobbyist) experts in CS. The geneticist is much better at C++ and OOP than me, the geologist knows a lot about 3d modelling and the whole GIS world, and the economist knows way more about DS, AI and statistics. Who am I to say they aren't experts? This kind of rigid division of field and expertise made no sense in university, and it only breaks apart more as we get older and more experienced.
> Are people as overconfident as the article claims, or are there many 'hobbyist' experts milling around? I did a Bachelor's in philosophy before switching to CS, and have been fascinated by IR/political theory since high school.
Heh, well, by coincidence, before I became a programmer I spent (too many) years as a PhD candidate in philosophy, and I'm skeptical about the extent to which undergraduates can be considered experts. ;-)
That was a long time ago, though, and despite my experience, I've undoubtedly fallen far behind the current work in the field.
Especially because good questions are more than simply asking about factoid X in Book Y. Good questions test if you really understood something and can transfer knowledge.
Coming up with such questions is not easy, and just because you did well on a test or "kept up with the field a bit" does not mean you can ASK such questions very well.
What if we flip this question around. Given what we’ve seen LLMs achieve today, if Bill Gates actually got an accurate read on their capabilities back then, what does that say about his expertise in biology? Maybe he got Dunning-Kreuger’d and made a lucky guess… or his assessment was accurate.
Given his track record and the state of AI today, I know which one I find more likely.
> Bill Gates was by all accounts an exceptional programmer at one point
Perhaps, but that point was in the 1970s, 50 years before he was evaluating OpenAI, and there were vastly fewer programmers in the 1970s, so "exceptional" then isn't necessarily exceptional now.
A footnote in the article mentions a crucial way he was exceptional: "Bill Gates went to one of the only high schools in the world that had a computer".
There were vastly fewer programmers in the 1970s, but there is no evidence whatsoever that the median skill or the top skill were lower than today.
The extra programmers of today have filled the voids in the distribution of programmers vs. skill, but in the best case for the present programmers they have not shifted the distribution towards a higher skill. If there was any shift in the distribution, it seems more likely that it was towards a lower skill.
I am pretty certain that any programmer who was exceptional in the 1970s would still be exceptional today.
Several decades ago, when I was very young, I reverse engineered a few Microsoft programs for CP/M, including the BASIC interpreter, the FORTRAN compiler and the FORTRAN run-time library.
At least the BASIC interpreter is likely to have included code written by Bill Gates. Given the hardware constraints, those programs were well written. They also included a lot of assembly language tricks that would not be used today, but which were justified in a program that had to run on very weak CPUs and using very little memory.
At that time, I considered those programs very instructive.
1) Although I think there is timeless inborn ability, I don't think there is timeless programming skill, irrespective of advances in technology. We clearly disagree about that, though: https://news.ycombinator.com/item?id=50498336
2) With regard to timeless inborn ability, I think it's obvious that you will end up with higher achievers if you start with a much larger population all working on the same activity.
> Do you think programers in the 70s would be considered unskilled nowadays?
Yes. C++ was created in 1985. JavaScript was created in 1995. I could go on and on. If a 70s programmer frozen in ice was unthawed today, that person would be unable to get a programming job.
The funny thing is that contemporary professional programmers who rely on Claude are already complaining that they've forgotten how to program, so how much could Bill Gates possibly remember 50 years later?
Any competent and experienced programmer who has learned a few diverse programming languages, even if those are only languages of the 60s, not even of the 70s, e.g. ALGOL 68, IBM PL/I, APL, LISP, SNOBOL, SIMULA 67, will be able to switch in a week or so to any other programming language of today, and reach the same level of competence as a programmer who has programmed only in that language for 10 years.
The job postings that require things like "5 years of experience with C++" or "5 years of experience with JavaScript" are really dumb, because anyone who really understands programming can do that in any programming language, after a few days needed to memorize its quirks, to avoid checking its specification continuously.
The number of innovations in programming languages that have been done after 1980 is extremely small in comparison with those done before 1980.
I disagree but consider the response too dismissive to even argue with seriously.
Actually, here's a serious argument: if you think of programming merely as knowing programming language syntax, you're missing the most important parts. Maybe we should phrase it more accurately as software engineering than computer programming. The problems that you face are vastly more difficult than satisfying a compiler or interpreter.
I would point to Microsoft's own recent global service outage. I guess they should have just called up old exceptional Bill to save them, eh?
I think you're saying the same thing. A good 70's developer would likely not have a lot of difficulties to fit in 2020 software world, precisely because software engineering and its challenges did not change much, even if the environment in which you have to do so did change a lot.
No, I did not say that. In fact I said the opposite of that.
It's a shocking misinterpretation after I wrote, "If a 70s programmer frozen in ice was unthawed today, that person would be unable to get a programming job."
Sorry. I thought you made the distinction between "knowing how to program" and "get a programming job". I disagree, then.
To quote another of your comments, you don't _think_ there is timeless programming skill. I do. Sure, there are areas of expertise (embedded, parallel, graphics, etc.), but the basic abilities (pre AI) stay the same.
I don't see why a good biologist, pianist, mathematician or scientist taken out of the 70s couldn't be good today. You seem to believe in some exceptionalism for computer science and software development. I don't see good foundations for this argument.
> I don't see why a good biologist, pianist, mathematician or scientist taken out of the 70s couldn't be good today.
I would note that you've moved the goalposts from "exceptional" to merely "good".
> You seem to believe in some exceptionalism for computer science and software development. I don't see good foundations for this argument.
It's simple: computing changes and advances much more rapidly than any of those other subjects. I addressed this point in another comment: "music has not become significantly more complex over the past 200 years. As far as I'm aware, pianos themselves haven't changed significantly since then." https://news.ycombinator.com/item?id=50498199
When Bill Gates cofounded Microsoft in 1975, personal computers did not yet exist; the Apple II arrived in 1977. LLMs did not exist, smartphones did not exist, the world wide web did not yet exist, and the precursor of the internet was just getting started. The computing world was entirely different. Bill's previous programming expertise is now obsolete.
I still don't get it. I don't try to be obtuse, I just don't get it. Sure, internet wasn't a thing. What does it change? Is learning the concept of a socket so hard that an exceptional (or good, whatever) programmer of the 70s could likely fail at this? Are the web languages impossible to master for someone who did not grow with internet?
Sure, no smartphone. And? Embedded was already a thing, and resources were infinitely more constrained. I guess you didn't have to write touch-enabled UIs. Again, something that an exceptional (or good) programmer of the 70s would likely not be able to learn?
How did exceptional (or good) programmers managed to stay relevant through those 50 years (which is just slightly longer than a typical career length)?
Note that LLMs are, in my opinion, a different thing. Similar to what cars did to horseshoes makers. You cannot pivot around this, however good you are.
> Are the web languages impossible to master for someone who did not grow with internet?
Of course not. Everyone programming today was born ignorant of the internet, and of everything else.
"Could Bill Gates learn contemporary programming if he put in the time and effort? Perhaps. The point is that he hasn't. Although he was a 1970s programming expert, he's a 2020s programming n00b." https://news.ycombinator.com/item?id=50498280
> How did exceptional (or good) programmers managed to stay relevant through those 50 years (which is just slightly longer than a typical career length)?
By putting in the work to keep their skills current.
They were not "magically transported", as you put it in another comment, from the beginning of their career to the end of their career. They had to go step by step, methodically.
Sure as we all know writing those Javascript CRUD apps like what the majority of today's programmers do is so much more difficult than what those losers in the 70s did.
> Sure as we all know writing those Javascript CRUD apps like what the majority of today's programmers do is so much more difficult than what those losers in the 70s did.
You're conflating two different things, (1) difficulty in principle with (2) practical knowledge and experience.
Could Bill Gates learn contemporary programming if he put in the time and effort? Perhaps. The point is that he hasn't. Although he was a 1970s programming expert, he's a 2020s programming n00b.
The sentence "X was an exceptional programmer" surely indicates that the exceptionality was in relation to his time period.
Are you going to say that someone like Salieri and Chopin were not technically exceptional because not that many people in the planet had a piano available?
> Are you going to say that someone like Salieri and Chopin were not technically exceptional because not that many people in the planet had a piano available?
There's a crucial difference: music has not become significantly more complex over the past 200 years. As far as I'm aware, pianos themselves haven't changed significantly since then. In contrast, computers and programming have changed dramatically since the 1970s. Whatever Gates did in the 1970s, it's not clear how 2020s Bill Gates, who stopped programming full-time decades ago, is qualified to evaluate contemporary programming.
1. Can someone _who haven't programmed for 50 years_ correctly evaluate current coding AI, and
2. Is what made a good programmer in the 70s the same as what make is good today to evaluate current coding AI.
If someone did competitive bike racing in 1970 and stopped since then, he probably forgot a lot of things and is not a good judge on current cycling. But if he were to be magically transported from that time, I don't see what he would lack. Sure, bikes are different (and better), nutrition is better understood, and so on. But the core job is the same.
> You conflate two different arguments: 1. Can someone _who haven't programmed for 50 years_ correctly evaluate current coding AI, and 2. Is what made a good programmer in the 70s the same as what make is good today to evaluate current coding AI.
I actually don't. See my other comment: "You're conflating two different things, (1) difficulty in principle with (2) practical knowledge and experience." https://news.ycombinator.com/item?id=50498280
> competitive bike racing
You cherry-picked an activity that depends primarily on the physical limits of the human body, which as far as I'm aware hasn't evolved significantly since the 1970s.
Still, training and sports science has evolved, as you note: "nutrition is better understood". (There's also the matter of doping and cheating.) Thus, I suspect that an exceptional racer magically transported from the 1970s might not be as exceptional now. Moreover, the Earth's population is larger now, and bike racing has become popularized by TV coverage, attracting more enthusiasts, not to mention more money, so the competition is now tougher. You can see this even more clearly in sports that were traditionally very white for socioeconomic reasons, such as golf and tennis: more non-white people are now competing in those sports, opening to a global population. At the top, the bar has been raised.
He wrote software for controlling hydroelectric dams when he was still in high school. At a time where the tooling was incredibly worse than it is now.
What's your definition of exceptional? Because that fits mine.
Computers, programming languages, and software in general were simple back then. It didn't take much to program them. You couldn't do much with a few KB of memory and a single-core single-thread CPU with basic instructions.
It took some amount of talent to squeeze something useful into computers with those constraints, but the upper limit on complexity also put an upper limit on how exceptional anything could be.
Bill Gates is/was an exceptional businessman. His technical abilities were nothing special.
By your definition, is John Carmack an exceptional programmer? After all, Wolfenstein3d is also simple, if you ignore the challenges of limited hardware and of being an early mover who has to invent lots of things from scratch. Who from that time period would qualify?
Exceptional is a relative term not an absolute one. I dislike Gates but you can't simply argue that he was not technically exceptional because the primitive tools he used capped how complex the software he wrote could be from a modern perspective of software complexity. It is ridiculous. By the same token, any software anyone living can possibly produce pales by the standards of a 2090 dev.
The reasonable take is that Gates was an exceptional dev for his era for the things he did with the things he had.
His code that we have seen has universally been good. It's written in a different era, with different constraints--"how much BASIC can one cram into 16K?"--but all computers ran on 8-bit microcomputer BASIC for a time, and Bill's was good.
He wrote that about claude in 2025. Do you think now bill gates is an exceptional programmer? You take 100 random programmes today and bill gates would write better code than all? I doubt that he is now an exceptional programmer. Maybe he was, but certainly not anymore. And how much code do you think he wrote as CEO of msft?
I have no idea if Bill still dusts off the keyboard or not. I can't say. What I can say confidently: if you had a time machine and could pair up 25 year old me against 25 year old Bill, he'd win in a hacking competition.
Be careful. I wrote an emulator for the IBM 7094 so I could run and understand Thompson's grep. Even though I wrote it in Lisp it was...painful.
Thompson uses self-modifying code, so my emulator had to handle that.
Thompson's code is incredibly clever, and back when he wrote it self-modifying code was pretty common. But by modern standards it would have been a maintenance nightmare.
I’d qualify this a bit by saying that in his time, it was exceptional to be a programmer at all. The barrier to entry was unimaginably higher than it is today.
I occasionally have to remind myself of that when I see 13-year-olds today do what I only did at 25. When I was 13, I was learning programming by typing in listings from flea market books, whereas today I’d use highly polished interactive tutorials. Of course people now progress much faster than at a time when it took 3 months of arcane research to make an Ethernet card work on Linux.
Bill Gates was 13 in 1968, one year before Unix. I'm not even sure what it meant to be a hobbyist programmer in 1968. Writing Fortran on paper and taking it to a local university to run?
In any case the parent's point absolutely stands - I came up in the 90s too and learning to program or make computers do things back then was largely a matter of reading books and talking to people. You had to really want it, because you had to track down and sift through the information.
Gates and Allen wrote an 8080 emulator on the Harvard PDP-10, then wrote Altair BASIC for the simulated 8080, which worked on the first try on a real Altair without their ever having seen one, after laboriously entering it with toggle switches at MITS in Albuquerque. <https://news.ycombinator.com/item?id=43579471>
The author's point is that "better than you" doesn't mean "superhuman", it just means "usefully good".
If we assume that you're 95th percentile at writing SQL, it's going to be amazing when companies can just copy-paste the 0.95 SQL dev instead of having to pay for that expertise -- but it doesn't really mean that AI improvement is going exponential, or that we've reach the singularity, or that AI will cure all disease and end human suffering or any of the other nonsense you see AI boosters predicting on this website every day.
Yeah I think the authors just mistaken. If you are top 5% or so in some skill and you see AI over a few years go from median to surpassing your skill level, you can use common sense and realize it’s going to get past the next 5%, and it has.
It feels like the author is making a bit of a big deal about bill gates declaring superhuman in January when it might take a year or so before it’s undeniable?
The author talked about programming specifically after biology. Even so, if you got a 5 on say AP Bio back in the day and have kept up with biology (professionally in Bills case or as a parent).. it seems like you would be a natural person to gauge how good AI is at AP exam level questions.
I think this is written forgetting a lot of the context of the time (I was at a relevant part of the industry to be present around some of the early “oh shit this thing works” moments).
It was absolutely not a given that next-token prediction would scale to the point that it could answer outside of its training domain (this is the point about “made up questions”, it was important to test it on material outside of the training set since the scale of training was yet-unheard-of at the time).
Further, the success of post-training on verifiable tasks (coding) was also a complete shock that changed the world overnight. LLMs jumped the “I can make code” to “I confidently can make code that solves your problem” chasm suddenly, and it has changed the industry.
For someone so invested in this from the early days (remember the scale of Microsoft’s commitment) it is entirely logical that testing things “on day one” would occur and this would be a much bigger shock compared to most people that learned of advances at the same time as the rest of the world. (There are huge delays between research capabilities and shipping)
This article first makes a point that Gates isn’t expert enough in biology to assess AIs capability to answer complex questions on the topic as being a breakthrough.
Then immediately goes on to say that his comments about AI coding are arrogant despite being an expert in that field with more experience than nearly anyone.
I would consider the average staff engineer, if appropriately titled, to be an expert in their field. If not a staff engineer then when exactly would one be considered an expert?
The funny thing is, even before AI staff engineers (especially in larger companies) often didn’t get to write code; most of the work was supervising other engineers who actually wrote the code for the architectures they designed… which was mostly docs. I used to joke that my favorite IDE’s were “IntelliJ, Google Docs and other engineers.”
I would be very skeptical that Gates has any experience in what we could call modern programming languages and architectures. When was the last time he was hands-on in the core development of an OS or major application? Things have changed significantly since like, 1985. Supervising teams of people writing complicated software? Sure. But even then, his role was abstracted away from the code base by at least 1993 or so.
Gates in the modern era would probably do great writing a small application designed to be extremely small and run on very limited resources. If your experience is targeting applications to run on systems with 2MB to 4MB of RAM at most and MS-DOS lower memory limitations, that's its whole own historical skill set and knowledge...
Gates has a lot of raw intelligence, but I'm not sure if he ever coded in an environment where keeping complexity under control was vital, instead of powering through with brute force. In other words, whether he ever programmed, himself, where "taste" and "style" mattered.
Brute force programming is the current era lol. An era where efficiency doesn't matter, and random programming (trying things until they work) is the norm
I always get the "ick" when I see someone successful in one domain assume they're automatically brilliant in all others. Like someone who made a fortune selling B2B SaaS going on a podcast talking nonsense about "quantum" or whatever.
I agree with you generally but this was a poor example of it. He wasn't claiming to be an expert in biology or that the AI would be if it did well on the rest. He was saying it was proving it could read and use information usefully. (And showing unbelievable hubris he said he could write a high school biology problem without a PhD in biology education)
> being an expert in that field with more experience than nearly anyone
Nothing annoys me more than business folks who try to claim street cred from their halcyon days as a programmer.
These folks are consistently the ones who make the worst decisions because they falsely believe their intuition of how software worked 20 years ago is valuable insight for technical decisions being made today.
People on the author's side of this debate just haven't seen the firsthand evidence yet. I can understand being skeptical until then, but they owe it to themselves to give late-2026 frontier models a try.
The lightbulb moment for me was when I gave Claude Code a tough reverse-engineering problem: understanding how a complex, proprietary encoding scheme worked, then building an encoder and decoder. There are some additional complicating factors that I can't disclose, because this was for work, but it was a tough problem.
For context, I've been doing RE for over 25 years. I'm not the best in the world, but I'm pretty good at it when I can find the time.
A coworker and I had spent about a week on the work, and I estimated it would take us another 2-3 to complete the work. We had figured out how about 3/4 of the messages were encoded, but the rest just didn't make sense.
I gave Claude Code our notes, and in 15 minutes it had finished figuring out the rest of the protocol and built a command-line decoder. I asked it to add an encoding feature, and in another ten minutes, it had done that as well. It tested all of its own code extensively using our corpus of real data.
The decoder worked perfectly on all of our existing captures as well as new data collected after that.
I had to make a small change to the encoder that was related to one of the things I can't disclose. I don't hold that against the model, because it didn't have access to the real product to test its output against. Making the change took maybe an hour because there was some trial-and-error involved.
That kind of capability is a genuine game-changer, especially when the interface is "describe the result you want in natural language". Ten years ago, I would have thought a truly useful natural language interface to a complex system was 20 to 30 years away at best.
Being able to quickly clone nearly all of the functionality of Adobe's entire product suite is another favourite example of mine.
This is by far the most disruptive technology I've seen introduced in my lifetime. A lot of people are using it for questionable purposes, but that always happens when people are figuring out how to make the best use of something new.
Of course if all you care about is yourself and you don't see the massive amounts of corruption, societal, and ecological harms going on, I would urge you to get your head out of the sand. You're on the chopping block like everyone else in the eyes of these corporations. If you're on the "in charge" side of things, well good luck with your moat and delusions man, legislation is coming for your business.
> I picked on Bill Gates above to illustrate the overconfidence effect
After having read your blog i can assert you've demonstrated that effect on yourself. Bill has all capability and credentials proven so we know this guy is an authority on software engineering topics, you have zero if i'm not mistaken.
I would bet his spectacularly good calls vastly outnumber his spectacularly bad calls. After stepping down as CEO, he was the chief architect and remains a technology advisor of the tech company that is currently one of the most valuable companies ever. That basically implies a long rarely-broken string of good calls. He has led software engineering at a scale only a handful of people ever have.
I would say he has more authority on software engineering topics than most people on earth, but that’s just me.
You are just focusing on the tech bit. Bill gates never was a very good person to begin with and then he did some stuff that pretty much offset whatever good he did.
As for software engineering: if you think Bill Gates is an authority in the field I would like to introduce you to Donald Knuth, Peter Norvig, Fabrice Bellard, Dennis Ritchie, Linus Torvalds and many others. Bill Gates wouldn't make the top 100.
Gates doesn't have the biology credentials. He's a pedophile, to top it off, so most probably that's where the article should have started with. It's telling that for most of the last 30 or so years the most wealthy person on this planet has been a pedophile, come to think of it maybe we (the human species) do deserve what's coming.
There's this thing people with strong opinions about something love to do: appeal to authority when it suites their agenda. This guy was once, a very long time ago in technical terms, very accomplished, so therefore everything he says now is more credible.
It's absolutely infuriating because it allows people with a lot of money tell you they know what they're talking about without proving it. Your money is your perceived effort, no matter how you acquired it.
Author is spot on on Bill Gates. By his own admission, his company essentially missed the coming of the Internet, and we all literally suffer today for it.
He missed the coming interconnectedness of the machines and instead presumed that every computer was going to be a fancy copy machine calculator (that will never talk to others, thus security is not needed).
billg wrote the “Internet Tidal Wave” memo in May of 1995! This was an era when the dominant enterprise IT infrastructure was heavyweight (Windows!) client/server and homes were just starting to connect to the internet via dialup en masse.
Microsoft proceeded to pivot so successfully that they monopolized the web browser market alongside winning a massively profitable position in enterprise “intranet” apps and TCP/IP-based servers.
If Microsoft had gone all in on the Internet in 1985 instead of DOS, Windows & building a dominant app platform + office suite, no one would remember them today.
The first part of the article makes sense in that:
In any system of competing agents (such as human beings) where the reward for performance can enhance performance, will always result in even minor random differentials in initial performance exponentially accumulating until one or a handful of individuals dominate. In such a system, only a small portion of success can be attributed to innate skills. So it's true that success in itself, while signaling fitness to survive, does not necessarily signal an outsized ability to make accurate judgements.
I'm not entirely clear what the second part of the article is trying to convey. Is it that highly successful individuals attribute their success entirely to their skill and therefore when a machine is able to replicate their skillset, they are surprised and consider the technology to be world-altering?
What I have seen first-hand is very talented individuals in one domain (tech) assume immediate authority in a novel domain (in my case it was local city planning). The thinking seems to be sort of the human equivalent of AGI? Note how confidently Gates talks about his expertise in novel biological science, for example.
Not doubting the intelligence of these individuals, just saying they sure tend to undervalue domain specific expertise. I don't know who Elon consulted about his cybertruck, but it wasn't truck people.
I do worry that AI exasperates this problem as a quick few queries and thoughtful questions have certainly given me over-confidence in a new subject. You don't know what you don't know.
But today’s agents are “superintelligent,” the same way that trains are “superlocomotive”—that is, faster than a running human. And they can carry more. Trains are just better at getting from point A to point B than humans.
That doesn’t mean trains are a superrace and humans are obsolete, just that we’ve built machines that can do something more effectively than our bodies are physically capable of, as usual.
Intelligence isn’t what makes us human. A human who can’t play chess or write a sonnet is still a human being.
They are called “agents” because they can, and do, perform actions autonomously on our behalf. Virtual agents are not a new thing.
Designing new algorithms is where the real skill is, but an average programmer will never do this, and even a 10x programmer will do it maybe a few times in their lifetime at most.
LLMs generate code that (often) works, but do they write "good code"?
Do you find LLM-generated code intuitive, readable, or elegant?
I'm not sure I do, which is why I find it puzzling when I hear/read people saying that LLMs write better code than they can, or at least code that's just as good (re-quoting Bill Gates from the article: "I could see that they are as good as I am").
It's now possible to "vibecode" entire applications without taking a single look at the code, but that’s not what my comment is about.
LLM-generated code isn't meant to be read by humans. LLMs specialize in generating text, and they're very good at it. But what they can't do is generate text as as if it were written by a human, for a human. I get this feeling from LLM-generated code, but also from most of the LLM-generated fiction, instructions, reports, etc.
What is the opposite of the Dunning-Kruger effect? Where you believe since you don’t know anything about a topic (eg biology), therefore nobody else can (you must have some incredible decades of research experience to have novel thoughts on it)?
It seems pretty clear to me that Bill was saying AI was as good as him a few months ago and now it is superhuman. This is an interview transcript, remember, not a written affidavit. Humans can switch focus mid stream.
The author is correct, although how he frames his perspective could be communicated better. Then again, that's judging his writing from a professional critique writer's opinion, this is an ordinary non-pro writer.
We have a serious problem in human society where people delude themselves routinely to believe expertise in one area magically translates to areas one has no experience. This is probably a human survival trait. It makes no sense, from a logical perspective: to venture into an area where one is educated enough to understand the danger of operating outside one's understanding is well ingrained by our educations, but we routinely ignore that like it does not exist. Perhaps this arrogance is how man's stupid will to force forward becomes our survival fitness.
The overconfidence effect is well documented and a known thing in light aircraft private aviation. People with education and good paying professional careers (doctors, lawyers, dentists, etc) who have the disposable income to buy a $300,000 aircraft and maintain it can easily become overconfident in their abilities. Because they're good at one thing in their life that requires a lot of education and training, they think it automatically extends to every other domain of knowledge that they set themselves to.
The original v-tailed Beechcraft Bonanza used to be known as the "v-tailed doctor killer".
Every IT project I've worked on for the last 25years have been successful even though usually 30% of IT project fail.
I'm smart enough to know that I can't make a distinction between my expertise or luck for the success of those project. But my ego wants it to be my expertise because I'm the only constant in those projects
There's something I find difficult when reading this piece. The thing is, I've been making a living as a programmer and I'm now in my seventh year, but programming wasn't actually my major. I majored in computational physics in university, jumped into programming on that basis, and taught myself programming. So does that mean I have no right to make up programming problems and ask questions? I mean, couldn't Bill Gates have studied biology hard and understood things outside his own field too?
Or is the theme of the piece that one ought to have epistemic humility?
But the thing is, this piece itself also makes claims about psychology, power theory, and human nature to some degree, which is ironic. But that can't be it. Because this piece has no epistemic humility in it.
Then, if we demand according to what this piece says, in the end it comes down to "no one can test AI outside the major they studied in university" — but honestly, isn't it just a matter of buying the textbooks and papers and testing AI with them?
> does that mean I have no right to make up programming problems and ask questions?
Of course not, but that's not what's being argued. If you believed you could authoritatively declare what AI is or is not, that would be different, though.
> couldn't Bill Gates have studied biology hard and understood things outside his own field too?
Yes but he would still be a dilettante. Belief to the contrary is more likely to be an indication of engineer's disease.
To be honest with you, I don't understand why you rate this piece so highly. This piece basically shows a strong self-contradiction. If it's due to human writing having self-contradiction, then this piece would be human. If that's the case, I think AI writing is better.
The point of the matter is that the intellectual humility the author of this piece advocates isn't present in this piece. What papers are cited for the psychological claims the author of this piece makes? Of course, there's no need to do that in a blog essay. But the target of this piece's criticism is the absolutization of one's own standards and epistemic humility, and the problem is that this piece also commits that contradiction. This is a matter of the piece's level. I respect the intellectual aesthetics of people who like this kind of writing, but it's not my taste.
Well said. I don't believe the author has any credentials or accolades in psychology or sociology, but they certainly have strong opinions on how other people should form opinions.
What I am seeing in the article is an unchecked case of cognitive dissonance. That's just the overwhelming sense I get. You identified it as self-contradiction. The reason I label it cognitive dissonance is that the author is arguing against something that they themselves are projecting; that subject matter experts in one domain are overconfident in another.
This article's self-fulfilling prophecy is that it will one day be used as an argument from authority, if it hasn't already.
For sure, Bill Gates didn’t study biology for four years in college and doesn’t have diploma. How come he can now ask questions about biology after being envolved in the field for fifteen (or how many) years? Get off biology’s lawn.
These kind of people are where they are because they become completely obsessed with a topic, so I can believe he studied hard, if he was obsessed with it.
Depends on the billionaires. Some, like Gates and Buffett, are introverts who've spent a lifetime doing lots of reading. I doubt they suddenly changed their personalities upon reaching some particular net worth.
But they do get to spend as much time as they like talking with leading experts in any field. I have a hard time seeing that as a disadvantage.
Whether Bill Gates is smart or not isn't my concern. I'm someone who reads his writing often, and I think his writing is worth reading. That said, on the other hand, this piece actually does contain a performative contradiction to some degree.
The theme of this piece is, in fact, "don't absolutize your own standards" — that successful people forget the contingency of their success, forget the situation and context of their judgment, and treat it as a universally correct judgment. But the problem lies in the writing itself that carries this piece's theme.
A doctor can smoke while telling a patient that smoking is bad — that's not a problem at all. The biggest contradiction in this piece is that, while warning against "absolutizing one's own standards outside one's own field," it reinforced the psychological parts without any argument or evidence. Honestly, everyone has that degree of contradiction in a homepage essay. So do I.
But separate from that, the difficulty in reading this piece is that if you're going to demand intellectual humility, you should at least be consistent within the text. You can criticize the act of reinforcing one's own standards outside one's field. The problem is that it's hard when, within the text, the author violates the very standards he set. I also tend to think this is to some degree a general human trait. Everyone has some logical leaps... it's not a bad thing, but that's how I am.
There’s no reason they can’t. To be honest, it seems to me that the author hasn’t studied hard here; I can’t imagine anyone being so dismissive if they have detailed personal experience of what the current crop of frontier models can do on whatever kind of intellectual task they feel is important.
It’s just plainly not true. Yes AI uses electricity but it’s not that large a percentage of global electricity use. A lot has been happening globally that effects energy use the last few years.
I also tend to blame any uptick on electing a president that explicitly ran on burning more coal and spent money to subsidize keeping otherwise obsolete coal online.
I keep hearing this AI water and energy panic stuff. I’m a believer in facts, so I go looking for it, and it’s just not there. Water use is similar to golf courses and light agriculture, though I can see it being a problem in places like the Southwest. The electricity use is decent but not at the levels people are losing their minds over.
It’s just not there.
I can see some of the complaints over noise and political corruption like special tax breaks and deals.
US coal use peaked in 2007 and only had a small uptick in 2025 mostly down to demand for electricity outstripping the ability to build new supply. It had little to do with current administration policy. In other circumstances the coal plants that went back online may have been converted to natural gas but it’s hard to say what then counter factual would have been.
I note that that chart doesn't contain data for 2026. It also doesn't contain data for 2030.
Unless something catastrophic happens, [0] construction four years out is effectively locked in. When what's being constructed is expected to increase CO2 emissions by ~50% after it's built, it's quite reasonable to assert that the LLM Industry has reversed our collective work on cutting CO2 emissions. It's exceedingly reasonable to bitch bitterly about it when those very same entities driving the construction today were screaming left and right about all of the initiatives they'd been championing to reduce power consumption and Save The Planet and whatnot just a few years ago.
[0] ..such as a fuckoff-huge bubble that's being used to justify said construction messily exploding...
The construction plans are nuts and it looks very much like a real estate bubble. I will be shocked if more than 1/4 of that gets built.
Chip efficiency gains will mean that by 2030 you’ll be getting 100X the inference throughput on half the power. All this construction is not necessary.
They're in line with what's needed to meet the revenue projections of the LLM companies. Your "100x the inference" assertion ignores the most expensive part of the work of creating SOTA LLMs... the "training". That is what the DCs are primarily being built to do.
Depends on how big the efficiency gains are. There is not infinite demand. Jevon’s paradox occurs when there is latent demand that is released at a lower price point.
I also found that these projections are 15 years ahead and assume nearly all power is from gas when battery and solar costs are still falling geometrically and data center demand has reignited modular nuclear interest.
I’m generally skeptical of all predictions of the form “look at this terrifying thing that happens if we extrapolate the current trends indefinitely!” See: “The Population Bomb” by Paul Erlich and countless other doom predictions of a similar nature.
Yeah my biggest concern is we have already tipped the climate and it’s currently ratcheting up to the next stable slot… one where we maybe lose Miami and experience huge agricultural region shifts that will destabilize governments and societies.
But hey. FAFO. We will live and adapt. Humans are like cockroaches, as a bio professor said to me once, and he explained that this is not an insult.
> Now Bill Gates surely has shown an interest in biology and, through his work with the Bill & Melinda Gates Foundation, has probably read a lot of articles and research in this field. But the hubris to think himself a subject matter expert able to make up advanced, novel questions in a scientific field outside his own and suitable to assess AI's true capabilities and then being "shocked" that it could answer these questions makes my point.
The author seems to have a weird fetish with “expertise” and gatekeeping opinions so that they can only be expressed by Ph.D.s. The above anecdote was about high school biology. Any educated adult should be more than capable of generating “novel” questions in areas they are familiar with. It’s bizarre to shout “dunning-krueger” about topics that are absolutely within the intellectual ambit of Bill Gates.
This piece reads very much like the conclusion was arrived at before any of the evidence, and even though the arguments were flimsy that didn’t stop the author from including them. Gee, I guess they’re unqualified to have an opinion on this topic and should just shut their mouth and let someone with a Ph.D. speak.
None of this matters. By the time truth out itself, the Kushner's, Gate's, Andreeson's, and Altman's of the world will have walked off with hundred of billions of our 401k money.
You are not compelled to invest in any indices. Pretty much all 401k plans have bond options. Even better, you can also go ahead and short as many AI companies as you want if you are so confident you have market-beating insight and join in on these supposed billions that are free for the taking. But I know, it’s a little harder to put your money where your mouth is than to put your mouth where the karma is.
Older posts on this site seem to have been interesting but the author is ultimately now captured by some distaste for AI and can no longer produce useful text.
* The Claude Delusion (2026-11-13)
* This is not sustainable (2026-10-27)
* 'Winning AI' (2026-10-01)
* Everybody's Lost Their Minds (2026-09-16)
Definitely a trap I need to keep in mind as I blog since I don’t want to become like that.
They are more inline with where society outside of tech is. Outside our bubble, people are very angry at tech bros, and we face a reckoning. These are in a way and attempt self critique and persuasion. I have one in the works as well
> or a share of an emerald mine from their fathers
This is so lazy and petty it made me stop reading. Whatever you think of Musk, it's trivially verifiable that the emerald mine thing is a myth.
And in case you think I'm some evil right-wing troll, here's the LA Times telling you the same thing:
> Over the years, Musk critics have accused him of getting a leg up in life because of money his father made from emerald mines. Isaacson, who interviewed Errol Musk, reports that Errol struck a black-market deal to receive emeralds from three mines in Zambia to cut in Johannesburg, but that Errol did not have an ownership stake in the mines. He reportedly earned $210,000 from those mines before the business collapsed in the 1980s.
> But Isaacson calls it a “myth” that Elon emigrated in 1989 with wealth from his father’s emerald business. Isaacson writes that Errol’s emerald business had become “worthless” years earlier, and that he only gave his son $2,000 in traveler’s checks when Elon Musk moved to Canada that year.
I mean...really. The LA Times hates reporting this so much that they put idiotic scare quotes around the words "myth" and "worthless", but they still have to print it, because it comes directly from one of the eminent biographers in the world today, who interviewed Musk's father.
> Anything approaching my skill level is superhuman
Or someone has the impression that Ai can code as well as them (and find errors) but at 10x the speed or more. They then conclude that human ability and superhuman speed is superhuman in total.
There is a documentary called Chimp Empire that follows societies of Chimpanzés in Uganda. You can see very nicely which human proclivities come from primate architecture. Social ladders to the extreme, bullying, nepotism, signalling, trust and alliances, tribe wars, survival, the alphas who get to produce a bunch of offspring but almost always die young from opponent beatings. Intelligence is everywhere and the patterns it has are everywhere. One Chimp finds a good new edible thing or tool to eat new edible things and the whole tribe learns about it, and everyone eats better. One chimp gets a new poisonous mushroom and tells others by dying - the others may even evolve to use the mushroom to hunt. The more chimps you have out there the more have to feed and hunt and find new tricks and if there are tricks to be found - great. If there aren’t, eventually the larger group goes against other chimp groups to get their foods the violent way.
You can look at this article like a chimp who envies on an alpha while having “Meister” in his domain name. You can look at it as descent to a group of chimps that have gone to pluck a field of toxic mushrooms.
When you look above the primate behaviors, the only question that matters is not if the new stick invented is better than having more chimps, but if the new stick will be used to grow the chimp universe or to shrink the # of chimps in the universe so one tribe gets the universe - under the premise of “all those chimps are ruining my universe”. It’s not whether it’s smarter or more powerful, but how its used. The confident will try more things than the doubtful. The scared will try less - will the stick be used to scare you into not trying?
If we had to actually be responsible and care about people or the world around us, we couldn't make these models as good as they are. Humanity needs this and they just don't understand. They'll understand when my ${insert-company-name} innovates on this ${insert-anti-human-bullshit-idea} for the betterment of mankind. The jobs? Nobody needs jobs and caring about that doesn't make me money. Security? Yeah, the industry has known how to do isolation for decades, but that takes away from the hundreds of billions of dollars to buy compute. We could avoid massive economic impact if we just wait for the electrical grid to catch up to power our datacenters? Nah, we care about money more than people or the environment.
It's all so short sighted and anyone supporting this behavior is anti-humanity.
Tendency to express overly confident opinions on every field possible is shared in many professional subcultures, including for instance, journalists, and philosophy graduates. And the last category is rarely successful in conventional sense. After you learned to measure your self-worth on a particular scale (intelligence in this case) you naturally will try to persuade everyone, and yourself in the first turn, that you are not worthless. So within the modern society as it is, it's natural bias for all nerds, whether we into tech, biz, or humanities. It just that if you happened to be rich and famous then you are more visible, and bloggers will judge exactly your overconfidence, and if you are a red-shirt peasant - you can't draw enough attention, and will be judged by your spouse.
That's just being human. If we step outside the tech echo chamber, many many people feel this way towards "tech bros." Do or don't be surprised when they give us a comeuppance.
Do you really believe the majority of people are indoctrinated and have no valid thoughts or feelings on these things?
If yes, what about you, compared to them, makes you immune to indoctrination?
My main counterpoint datum is the US midterm election exit polls. People said affordability and corruption are their top issues and that they are interconnected. Tech bros are their exemplar de jour - with good reason.
> Do you really believe the majority of people are indoctrinated and have no valid thoughts or feelings on these things?
If half the population consume the same sort of media that's all saying the same thing then they're very likely to believe the same thing. They will believe they noticed something, when in fact they were told it over and over. Pick whichever half you like. Just as I don't trust a nationalist's opinion on immigration, I don't trust a Marxist's opinion on the wealthy.
As for "valid feelings" I agree this is about feelings and not thoughts, but I don't know what a valid or invalid feeling is.
> If half the population consume the same sort of media that's all saying the same thing then they're very likely to believe the same thing.
The naivety... to assume people agree with or support everything they read or watch. How are we to know what others think without consuming their content? How are we to persuade them of weak points in their arguments if we do not know the foundations?
What indoctrination have you yourself been subjected to? You seem to be stuck on a bipolar view, defined by the extremes (a minority), in a nuanced world that is growing increasingly tired of the extremes, their reductionist perspectives, and their bickering.
My favourite diss for all overconfident programmers is, if all these people are so brilliant why does so much software suck? But yes anyone thrust into the spotlight tends to think they’re the cat’s pyjamas.
> "Take note of the emphasis I added: the very notion that something else could be "as good as I am" is, first of all, hard to believe and secondly necessarily means that it's "superhuman".
Unironically, I recommend psychedelics. The right experience will make you aware of just how tiny a part of a vast universe you are -- and obliterate any sense of hubris.
Being "human" is ill-defined. Being "super-human" even more. LLMs abilities are superior to humans in many ways, sure. So does my calculator. So does an excavator.
LLMs are "super-humans" in novel ways, sure. But machines having superior abilities than humans' is nothing new. Nothing.
This is the exact kind of article I find deeply self-important and pretentiously delusional, ironically enough.
Sure, the biology point is fair. The rest is very silly. It moving on to say Bill Gates is therefore wrong to fear the pace of AI improvement is extremely silly.
> This narrative of agency conveniently also relieves you of responsibility. You didn't fail to properly restrict a potentially malicious program you trained to hack other systems with persistence. No, the "agents" went "rogue".
This will be the thing that really hurts the frontier labs. I believe they will be sued into oblivion and regulated in surprising ways.
"the very notion that something else could be "as good as I am" is, first of all, hard to believe and secondly necessarily means that it's "superhuman". That man is not lacking self-esteem, no sirree, Bob. "
I like that the article just tries to pass off a computer program coding at the level of humans (not to mention solving Millennium Problems) as something that should be just be totally unsurprising. Bill Gates is just a dumb arrogant tech bro to be surprised that a neural network exceeds his abilities at coding.
I'm trying to find the exact clip, but there's a segment of an interview where Elon Musk explains why he finds it likely that we are living in a simulation, and part of his evidence is how unlikely he finds it to be him: He's the richest man in the world, the first trillionaire, he's influencing geopolitics and launching space rockets.
He finds it so astounding to be himself, to feel like the Main Character of the World that he considers this evidence that the world he experiences is a simulation. The more humbling proposition -- that the world is largely random and he just happens to be the guy who kept rolling sixes -- is less compelling.
I want to preface what I'm about to say with the fact that I believe super intelligence is (by some reasonable definition) more likely than not to arrive some time next year.
However, today's models have extremely jagged intelligence even within fields they're extremely capable in.
Like most people here, I use Claude and other models daily and I used them primarily in the context of building a very complex software project. Claude is brilliant at writing code at, in very clean and well defined codebases, where its being asked to build something that fits well within the preexisting patterns.
Someone non-technical who does a lot of vibe coding recently asked why I couldn't just tell Claude to go build some feature into the project and call it a day? And it's genuinely hard to explain to people who are not both experts broadly in the field and experts in the specifics of the problem why this such a bad idea. And annoyingly it's not that Claude won't produce something that works, it will produce something that makes several extremely bad assumptions and defensively codes in those assumptions. And even when you explain this, the question then changes to, "yeah, but you could just ask Claude to fix that".
My default way of working today is to start 90% of my projects by simply asking in a few paragraphs what I want, seeing what Claude builds then spending half a day working through it, explaining all the wrong assumptions it's made, then reaching a clean and maintainable solution at the end.
However, I have been on the other side of this and I've felt magic of Claude when I've got it to write code I don't really understand. On the surface it seems to be able to do everything I ask stupidly fast. It's better than any human you could ever work with. But who knows what it's doing under the hood... My guess is that you simply can't keep building like that for long because while it will do everything you ask, the foundations of what it's building on are basically non-existent – and anyone whose worked on a serious software project before knows the foundations of any software are by far the most important things in the long-term robustness and maintainability of the project.
I guess what I'm saying is that many people who are non-experts in the field or non-exports in the specific problem within the fields they're asking AI to do things are largely delusional about what AI can and can't do. It absolutely can create a simple CRUD app, but it will not build a complicated distributed system and process millions of requests a day with five 9s of uptime.
That's not to say it will never happen. I think it will, but there's some things that need to be figured out first.
I was working with someone earlier this week who was telling me about how he convinced GPT-6.1 his name was an an XSS attack string. I don't think you could convince 1 in a million humans that your legal name is genuinely <script>alert("hello!");</script> and yet these models are supposed to be experts in domains like cyber security and super intelligent? It's honestly staggering how stupid they can be whilst also being so competent at a surface level.
This article articulates several thoughts I share with the author well. If there is anything people in the technology industry lack, it's intellectual humility.
That, and, they are pitifully ahistorical people. Today's industry leaders are not sufficiently schooled in constructivism. No, I don't mean they all need to become radical constructivists, but they should all at least gain a passing familiarity with Foucault before they continue fucking with humanity's social mores and environments with impunity.
They won't, of course, because they are decidedly unreflective (see Andreessen), unphilosophical people. They are, oftentimes, the marquee examples of 'soulless' people fueled only by the incentive structures put before them by the economy. Money. Clout. "Progress". It's telling that, beyond the many examples of hubris like that of Gates, basically zero technologists have come out and examined the unspoken assumptions behind such terms as "progress", "alignment", "intelligence" and the difficult social problems fixing these terms would entail. Moreover, they interpret all of these terms using some reified capitalistic gloss and go on their merry way, because, in spite of their constant proclamations to the contrary, most of them are not, in fact, very intelligent beyond being savvy businessmen.
The employees bear the brunt of actual technical intelligence. Leadership bears little more than a passing ability to navigate an economic structure that, let's face it, is already very forgiving to them and essentially places little to no responsibility on them after certain levels of scale are achieved. But none of that scale is possible without the vast legions of employees. Oftentimes the 'genius idea' is about 0.5% of the actual success of an endeavor, yet we cling to an old "great men of history" form of thinking and allow the public to prop up these individuals as though they are demigods.
Writing like this is corrosive. The most effective takeaway that it contains (about overconfidence) is banal. Everything else is an aggrieved deconstruction of—out of all things—a conversation between Ezra Klein and Bill Gates for the New York Times.
The true integrity and value of this blog post depends on your own interpretation of the author's interpretation of the hour-long podcast plus his supporting snipes toward Gates, Musk, Trump and other Tech Bros (read: Bad Nerds).
As an appendix I want to link to this submission from 3 months ago:
Ah yes, the professor from Hoboken is here to teach us that tech bros are delusional, and it’s really professors from Hoboken who know what is actually going on.
Biases and heuristics have become somewhat mainstream “intellectualism”, but just like people using the words prolific and myriad incorrectly, is leveraged here to a false conclusion.
The anti-AI narrative continues, to the detriment of those who listen to its self-destructive guidance that equates excessive enthusiasm with delusion.
Both the author's and your perspectives can be wrong at the same time, yet have elements of truth. Certainly the phrase "coastal elites" did not come from nothing. At the same time, the critiques have their own form of intellectual elitism, in essence doing the same thing they critique.
> The anti-AI narrative continues, to the detriment of those who listen to its self-destructive guidance
Can you expand on your view of the narrative (which one) and why it is self-destructive (which one)?
The narrative of AI being of illusory value, only appealing to the delusional tech elite, is one that serves only to soothe the emotions of those who are unwilling to embrace reality.
That's not the narrative that I read in the post. It was people who excel in on area believing their expertise translates to other things. The leaders of Ai are doing this
he presents the idea of Bill Gates observing an OpenAI model a. doing "complex" biology problems, b. some coding problems, and then based on his assumption that Bill Gates knows rudimentary biology, and used to also write code, the fact that Bill Gates is impressed with the OpenAI model means Bill Gates thinks he has superhuman biology and coding skills. This simply does not follow.
This would be like if I went in my garage, spent several weeks with the 3d printer and CNC machine to build a robot that can "dance", then I made a video of me dancing about as well as your average dad at a wedding along with my dancing robot and I said "this thing can dance better than me!", therefore: "Ha, your robot sucks! You must think you're Baryshnikov if you call that dancing". I mean this is kind of sad.
Slightly more than a couple of years ago, just observing an LLM coherently doing work at the academic level of a sixth grader was brand new to all of us. Which was objectively impressive. It doesnt matter "so what? anyone can do 6th grade math"....this..is not..the point...
edit: the point they want to make, that these people are not qualified to make dire predictions about "superintelligence", and that they see themselves fit to determine "superintelligence" based on watching the robots be smarter than them, is one I generally agree with, and their certainty originates from a kind of hubris. but it's not a hubris you can assign to the general LLM-using population as this seems to be doing. Most people using LLMs think the "superintelligence" thing is a load of bunk (probably moreso than the general population who seem to be cowering in terror).
I am no fan of Bill Gates. He's pedophile adjacent, in my *opinion.
But I was there. He worked really, really fucking hard. As did most of the early crowd. If you're asking yourself how people back then worked so hard, just realize that there are drugs that can help you do that.
I find the authors point not very compelling.. Bill Gates was by all accounts an exceptional programmer at one point and then spent a long time evaluating software engineers. He seems like a natural person to gauge AI progress in coding?
Around when AI was getting much better at SQL I was writing SQL everyday at work and had been for years. I don’t think it would’ve been hubris for me to judge that it was getting really good and would shortly be super human at SQL. It would’ve been correct anyway.
He also tries to dunk on Gates by saying he claimed he produced novel problems in science to test AI.
I don’t think the author realizes that “AP” is an exam for American high schoolers. Gates is only claiming he made new test questions at a high school+ level that wouldn’t have been in the training set for AI. I don’t see how it’s so unbelievable he could do that.
> Gates is only claiming he made new test questions at a high school+ level that wouldn’t have been in the training set for AI. I don’t see how it’s so unbelievable he could do that.
It’s unbelievable because Gates is neither a biology exam author nor a biology textbook author, so how would he even know what’s in the training set for AI? To know, you would need to be an experienced biology teacher and survey the pedagogical literature.
If you did well on AP Bio in the distant past and have kept up with the field of biology like Gates it is normal you could ask some high school exam level questions.
When I was studying for AP Calculus or Literature etc I’m sure I could’ve made decent sample questions.
Nobody is disputing whether Gates could come up with some exam questions. They're disputing whether Gates could come up with novel exam questions that weren't in the AI training data.
Maybe he was into biology for a hobby. Would fit his character, much like half of HNers are probably near-experts in some random field they haven't had formal training in. It's not unusual.
And would fit the fact that he funded biotech R&D too.
> much like half of HNers are probably near-experts in some random field they haven't had formal training in
More like half of HNs believe they're near-experts in some random field.
This is the crux though, isn't it? Are people as overconfident as the article claims, or are there many 'hobbyist' experts milling around? I did a Bachelor's in philosophy before switching to CS, and have been fascinated by IR/political theory since high school. While I could not hope to learn it all, I can hold a good conversation with a researcher in either philosophy or IR, especially if it intersects with a topic of my core expertise.
To flip it around, I have friends who I would consider (hobbyist) experts in CS. The geneticist is much better at C++ and OOP than me, the geologist knows a lot about 3d modelling and the whole GIS world, and the economist knows way more about DS, AI and statistics. Who am I to say they aren't experts? This kind of rigid division of field and expertise made no sense in university, and it only breaks apart more as we get older and more experienced.
> Are people as overconfident as the article claims, or are there many 'hobbyist' experts milling around? I did a Bachelor's in philosophy before switching to CS, and have been fascinated by IR/political theory since high school.
Heh, well, by coincidence, before I became a programmer I spent (too many) years as a PhD candidate in philosophy, and I'm skeptical about the extent to which undergraduates can be considered experts. ;-)
That was a long time ago, though, and despite my experience, I've undoubtedly fallen far behind the current work in the field.
Especially because good questions are more than simply asking about factoid X in Book Y. Good questions test if you really understood something and can transfer knowledge.
Coming up with such questions is not easy, and just because you did well on a test or "kept up with the field a bit" does not mean you can ASK such questions very well.
What if we flip this question around. Given what we’ve seen LLMs achieve today, if Bill Gates actually got an accurate read on their capabilities back then, what does that say about his expertise in biology? Maybe he got Dunning-Kreuger’d and made a lucky guess… or his assessment was accurate.
Given his track record and the state of AI today, I know which one I find more likely.
> Bill Gates was by all accounts an exceptional programmer at one point
Perhaps, but that point was in the 1970s, 50 years before he was evaluating OpenAI, and there were vastly fewer programmers in the 1970s, so "exceptional" then isn't necessarily exceptional now.
A footnote in the article mentions a crucial way he was exceptional: "Bill Gates went to one of the only high schools in the world that had a computer".
There were vastly fewer programmers in the 1970s, but there is no evidence whatsoever that the median skill or the top skill were lower than today.
The extra programmers of today have filled the voids in the distribution of programmers vs. skill, but in the best case for the present programmers they have not shifted the distribution towards a higher skill. If there was any shift in the distribution, it seems more likely that it was towards a lower skill.
I am pretty certain that any programmer who was exceptional in the 1970s would still be exceptional today.
Several decades ago, when I was very young, I reverse engineered a few Microsoft programs for CP/M, including the BASIC interpreter, the FORTRAN compiler and the FORTRAN run-time library.
At least the BASIC interpreter is likely to have included code written by Bill Gates. Given the hardware constraints, those programs were well written. They also included a lot of assembly language tricks that would not be used today, but which were justified in a program that had to run on very weak CPUs and using very little memory.
At that time, I considered those programs very instructive.
1) Although I think there is timeless inborn ability, I don't think there is timeless programming skill, irrespective of advances in technology. We clearly disagree about that, though: https://news.ycombinator.com/item?id=50498336
2) With regard to timeless inborn ability, I think it's obvious that you will end up with higher achievers if you start with a much larger population all working on the same activity.
Do you think programers in the 70s would be considered unskilled nowadays?
Today's programmers definitely would be considered unskilled in the 70s.
> Do you think programers in the 70s would be considered unskilled nowadays?
Yes. C++ was created in 1985. JavaScript was created in 1995. I could go on and on. If a 70s programmer frozen in ice was unthawed today, that person would be unable to get a programming job.
The funny thing is that contemporary professional programmers who rely on Claude are already complaining that they've forgotten how to program, so how much could Bill Gates possibly remember 50 years later?
Any competent and experienced programmer who has learned a few diverse programming languages, even if those are only languages of the 60s, not even of the 70s, e.g. ALGOL 68, IBM PL/I, APL, LISP, SNOBOL, SIMULA 67, will be able to switch in a week or so to any other programming language of today, and reach the same level of competence as a programmer who has programmed only in that language for 10 years.
The job postings that require things like "5 years of experience with C++" or "5 years of experience with JavaScript" are really dumb, because anyone who really understands programming can do that in any programming language, after a few days needed to memorize its quirks, to avoid checking its specification continuously.
The number of innovations in programming languages that have been done after 1980 is extremely small in comparison with those done before 1980.
> switch in a week or so
> after a few days
I disagree but consider the response too dismissive to even argue with seriously.
Actually, here's a serious argument: if you think of programming merely as knowing programming language syntax, you're missing the most important parts. Maybe we should phrase it more accurately as software engineering than computer programming. The problems that you face are vastly more difficult than satisfying a compiler or interpreter.
I would point to Microsoft's own recent global service outage. I guess they should have just called up old exceptional Bill to save them, eh?
I think you're saying the same thing. A good 70's developer would likely not have a lot of difficulties to fit in 2020 software world, precisely because software engineering and its challenges did not change much, even if the environment in which you have to do so did change a lot.
No, I did not say that. In fact I said the opposite of that.
It's a shocking misinterpretation after I wrote, "If a 70s programmer frozen in ice was unthawed today, that person would be unable to get a programming job."
Sorry. I thought you made the distinction between "knowing how to program" and "get a programming job". I disagree, then.
To quote another of your comments, you don't _think_ there is timeless programming skill. I do. Sure, there are areas of expertise (embedded, parallel, graphics, etc.), but the basic abilities (pre AI) stay the same.
I don't see why a good biologist, pianist, mathematician or scientist taken out of the 70s couldn't be good today. You seem to believe in some exceptionalism for computer science and software development. I don't see good foundations for this argument.
> I don't see why a good biologist, pianist, mathematician or scientist taken out of the 70s couldn't be good today.
I would note that you've moved the goalposts from "exceptional" to merely "good".
> You seem to believe in some exceptionalism for computer science and software development. I don't see good foundations for this argument.
It's simple: computing changes and advances much more rapidly than any of those other subjects. I addressed this point in another comment: "music has not become significantly more complex over the past 200 years. As far as I'm aware, pianos themselves haven't changed significantly since then." https://news.ycombinator.com/item?id=50498199
When Bill Gates cofounded Microsoft in 1975, personal computers did not yet exist; the Apple II arrived in 1977. LLMs did not exist, smartphones did not exist, the world wide web did not yet exist, and the precursor of the internet was just getting started. The computing world was entirely different. Bill's previous programming expertise is now obsolete.
I still don't get it. I don't try to be obtuse, I just don't get it. Sure, internet wasn't a thing. What does it change? Is learning the concept of a socket so hard that an exceptional (or good, whatever) programmer of the 70s could likely fail at this? Are the web languages impossible to master for someone who did not grow with internet? Sure, no smartphone. And? Embedded was already a thing, and resources were infinitely more constrained. I guess you didn't have to write touch-enabled UIs. Again, something that an exceptional (or good) programmer of the 70s would likely not be able to learn?
How did exceptional (or good) programmers managed to stay relevant through those 50 years (which is just slightly longer than a typical career length)?
Note that LLMs are, in my opinion, a different thing. Similar to what cars did to horseshoes makers. You cannot pivot around this, however good you are.
> Are the web languages impossible to master for someone who did not grow with internet?
Of course not. Everyone programming today was born ignorant of the internet, and of everything else.
"Could Bill Gates learn contemporary programming if he put in the time and effort? Perhaps. The point is that he hasn't. Although he was a 1970s programming expert, he's a 2020s programming n00b." https://news.ycombinator.com/item?id=50498280
> How did exceptional (or good) programmers managed to stay relevant through those 50 years (which is just slightly longer than a typical career length)?
By putting in the work to keep their skills current.
They were not "magically transported", as you put it in another comment, from the beginning of their career to the end of their career. They had to go step by step, methodically.
Sure as we all know writing those Javascript CRUD apps like what the majority of today's programmers do is so much more difficult than what those losers in the 70s did.
> Sure as we all know writing those Javascript CRUD apps like what the majority of today's programmers do is so much more difficult than what those losers in the 70s did.
You're conflating two different things, (1) difficulty in principle with (2) practical knowledge and experience.
Could Bill Gates learn contemporary programming if he put in the time and effort? Perhaps. The point is that he hasn't. Although he was a 1970s programming expert, he's a 2020s programming n00b.
The sentence "X was an exceptional programmer" surely indicates that the exceptionality was in relation to his time period.
Are you going to say that someone like Salieri and Chopin were not technically exceptional because not that many people in the planet had a piano available?
> Are you going to say that someone like Salieri and Chopin were not technically exceptional because not that many people in the planet had a piano available?
There's a crucial difference: music has not become significantly more complex over the past 200 years. As far as I'm aware, pianos themselves haven't changed significantly since then. In contrast, computers and programming have changed dramatically since the 1970s. Whatever Gates did in the 1970s, it's not clear how 2020s Bill Gates, who stopped programming full-time decades ago, is qualified to evaluate contemporary programming.
You conflate two different arguments:
1. Can someone _who haven't programmed for 50 years_ correctly evaluate current coding AI, and 2. Is what made a good programmer in the 70s the same as what make is good today to evaluate current coding AI.
If someone did competitive bike racing in 1970 and stopped since then, he probably forgot a lot of things and is not a good judge on current cycling. But if he were to be magically transported from that time, I don't see what he would lack. Sure, bikes are different (and better), nutrition is better understood, and so on. But the core job is the same.
> You conflate two different arguments: 1. Can someone _who haven't programmed for 50 years_ correctly evaluate current coding AI, and 2. Is what made a good programmer in the 70s the same as what make is good today to evaluate current coding AI.
I actually don't. See my other comment: "You're conflating two different things, (1) difficulty in principle with (2) practical knowledge and experience." https://news.ycombinator.com/item?id=50498280
> competitive bike racing
You cherry-picked an activity that depends primarily on the physical limits of the human body, which as far as I'm aware hasn't evolved significantly since the 1970s.
Still, training and sports science has evolved, as you note: "nutrition is better understood". (There's also the matter of doping and cheating.) Thus, I suspect that an exceptional racer magically transported from the 1970s might not be as exceptional now. Moreover, the Earth's population is larger now, and bike racing has become popularized by TV coverage, attracting more enthusiasts, not to mention more money, so the competition is now tougher. You can see this even more clearly in sports that were traditionally very white for socioeconomic reasons, such as golf and tennis: more non-white people are now competing in those sports, opening to a global population. At the top, the bar has been raised.
> I find the authors point not very compelling. Bill Gates...
The message was more abstract, why focus on one (poor) example?
He was not an exceptional programmer.
He wrote software for controlling hydroelectric dams when he was still in high school. At a time where the tooling was incredibly worse than it is now.
What's your definition of exceptional? Because that fits mine.
Computers, programming languages, and software in general were simple back then. It didn't take much to program them. You couldn't do much with a few KB of memory and a single-core single-thread CPU with basic instructions.
It took some amount of talent to squeeze something useful into computers with those constraints, but the upper limit on complexity also put an upper limit on how exceptional anything could be.
Bill Gates is/was an exceptional businessman. His technical abilities were nothing special.
By your definition, is John Carmack an exceptional programmer? After all, Wolfenstein3d is also simple, if you ignore the challenges of limited hardware and of being an early mover who has to invent lots of things from scratch. Who from that time period would qualify?
Exceptional is a relative term not an absolute one. I dislike Gates but you can't simply argue that he was not technically exceptional because the primitive tools he used capped how complex the software he wrote could be from a modern perspective of software complexity. It is ridiculous. By the same token, any software anyone living can possibly produce pales by the standards of a 2090 dev.
The reasonable take is that Gates was an exceptional dev for his era for the things he did with the things he had.
His code that we have seen has universally been good. It's written in a different era, with different constraints--"how much BASIC can one cram into 16K?"--but all computers ran on 8-bit microcomputer BASIC for a time, and Bill's was good.
He wrote that about claude in 2025. Do you think now bill gates is an exceptional programmer? You take 100 random programmes today and bill gates would write better code than all? I doubt that he is now an exceptional programmer. Maybe he was, but certainly not anymore. And how much code do you think he wrote as CEO of msft?
I have no idea if Bill still dusts off the keyboard or not. I can't say. What I can say confidently: if you had a time machine and could pair up 25 year old me against 25 year old Bill, he'd win in a hacking competition.
> “You take 100 random programmes today…”
I’m not taking a side on Bill’s skilz. But you can’t compare the two populations so blithely.
There’s something like +6x growth in the industry from the 80’s to 2014 in the US Census alone.
And by my little Google AI search, it might be 1:70 worldwide. I’m no statistician, but maybe pick 10 programmers from 1980 and 700 worldwide today.
https://www.census.gov/content/dam/Census/library/publicatio...
+1
he was great but not carmack, bellard, cutler great.
he was an exceptional bully
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How do we define “exceptional programmer”? What makes a programmer “exceptional”?
The benchmark is Ken Thompson
Be careful. I wrote an emulator for the IBM 7094 so I could run and understand Thompson's grep. Even though I wrote it in Lisp it was...painful.
Thompson uses self-modifying code, so my emulator had to handle that.
Thompson's code is incredibly clever, and back when he wrote it self-modifying code was pretty common. But by modern standards it would have been a maintenance nightmare.
https://dl.acm.org/doi/epdf/10.1145/363347.363387
I’d qualify this a bit by saying that in his time, it was exceptional to be a programmer at all. The barrier to entry was unimaginably higher than it is today.
I occasionally have to remind myself of that when I see 13-year-olds today do what I only did at 25. When I was 13, I was learning programming by typing in listings from flea market books, whereas today I’d use highly polished interactive tutorials. Of course people now progress much faster than at a time when it took 3 months of arcane research to make an Ethernet card work on Linux.
Wasn’t Unix already a thing for years at this point? Also LISP machine and smalltalk.
Availability is a thing sure, which increase opportunities, but that’s not saying the talent spectrum is different.
Bill Gates was 13 in 1968, one year before Unix. I'm not even sure what it meant to be a hobbyist programmer in 1968. Writing Fortran on paper and taking it to a local university to run?
In any case the parent's point absolutely stands - I came up in the 90s too and learning to program or make computers do things back then was largely a matter of reading books and talking to people. You had to really want it, because you had to track down and sift through the information.
Gates and Allen wrote an 8080 emulator on the Harvard PDP-10, then wrote Altair BASIC for the simulated 8080, which worked on the first try on a real Altair without their ever having seen one, after laboriously entering it with toggle switches at MITS in Albuquerque. <https://news.ycombinator.com/item?id=43579471>
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The author's point is that "better than you" doesn't mean "superhuman", it just means "usefully good".
If we assume that you're 95th percentile at writing SQL, it's going to be amazing when companies can just copy-paste the 0.95 SQL dev instead of having to pay for that expertise -- but it doesn't really mean that AI improvement is going exponential, or that we've reach the singularity, or that AI will cure all disease and end human suffering or any of the other nonsense you see AI boosters predicting on this website every day.
Yeah I think the authors just mistaken. If you are top 5% or so in some skill and you see AI over a few years go from median to surpassing your skill level, you can use common sense and realize it’s going to get past the next 5%, and it has.
It feels like the author is making a bit of a big deal about bill gates declaring superhuman in January when it might take a year or so before it’s undeniable?
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He was evaluation biology test though. Reading comprehension zero.
The author talked about programming specifically after biology. Even so, if you got a 5 on say AP Bio back in the day and have kept up with biology (professionally in Bills case or as a parent).. it seems like you would be a natural person to gauge how good AI is at AP exam level questions.
I think this is written forgetting a lot of the context of the time (I was at a relevant part of the industry to be present around some of the early “oh shit this thing works” moments).
It was absolutely not a given that next-token prediction would scale to the point that it could answer outside of its training domain (this is the point about “made up questions”, it was important to test it on material outside of the training set since the scale of training was yet-unheard-of at the time).
Further, the success of post-training on verifiable tasks (coding) was also a complete shock that changed the world overnight. LLMs jumped the “I can make code” to “I confidently can make code that solves your problem” chasm suddenly, and it has changed the industry.
For someone so invested in this from the early days (remember the scale of Microsoft’s commitment) it is entirely logical that testing things “on day one” would occur and this would be a much bigger shock compared to most people that learned of advances at the same time as the rest of the world. (There are huge delays between research capabilities and shipping)
This article first makes a point that Gates isn’t expert enough in biology to assess AIs capability to answer complex questions on the topic as being a breakthrough.
Then immediately goes on to say that his comments about AI coding are arrogant despite being an expert in that field with more experience than nearly anyone.
Unsure how to interpret that.
He doesn't have more programming experience than your average staff engineer. When was the last time he wrote a meaningful amount of code?
Being CEO does not involve a lot of coding. Yes he was an expert 40 years ago, but a lot has happened in 40 years
I would consider the average staff engineer, if appropriately titled, to be an expert in their field. If not a staff engineer then when exactly would one be considered an expert?
Speaking as a staff engineer, none of us have written much code for a while, either. Guess no experts exist.
The funny thing is, even before AI staff engineers (especially in larger companies) often didn’t get to write code; most of the work was supervising other engineers who actually wrote the code for the architectures they designed… which was mostly docs. I used to joke that my favorite IDE’s were “IntelliJ, Google Docs and other engineers.”
I would be very skeptical that Gates has any experience in what we could call modern programming languages and architectures. When was the last time he was hands-on in the core development of an OS or major application? Things have changed significantly since like, 1985. Supervising teams of people writing complicated software? Sure. But even then, his role was abstracted away from the code base by at least 1993 or so.
Gates in the modern era would probably do great writing a small application designed to be extremely small and run on very limited resources. If your experience is targeting applications to run on systems with 2MB to 4MB of RAM at most and MS-DOS lower memory limitations, that's its whole own historical skill set and knowledge...
Gates has a lot of raw intelligence, but I'm not sure if he ever coded in an environment where keeping complexity under control was vital, instead of powering through with brute force. In other words, whether he ever programmed, himself, where "taste" and "style" mattered.
Brute force is not an option when you have 640Kb of RAM and your processor's clock runs at single-digit MHz.
Yes! Even 640K was a crazy luxury. Microsoft BASIC ran with a tiny fraction of that.
I mean brainpower instead of good design to manage the complexity. Not brute force algorithms.
Brute force programming is the current era lol. An era where efficiency doesn't matter, and random programming (trying things until they work) is the norm
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> Gates isn’t expert enough in biology
I always get the "ick" when I see someone successful in one domain assume they're automatically brilliant in all others. Like someone who made a fortune selling B2B SaaS going on a podcast talking nonsense about "quantum" or whatever.
I agree with you generally but this was a poor example of it. He wasn't claiming to be an expert in biology or that the AI would be if it did well on the rest. He was saying it was proving it could read and use information usefully. (And showing unbelievable hubris he said he could write a high school biology problem without a PhD in biology education)
By Gates' own admission, he hasn't had a new line of code ship in a product for over 41 years.
> Unsure how to interpret that.
Then ask Claude!
> being an expert in that field with more experience than nearly anyone
Nothing annoys me more than business folks who try to claim street cred from their halcyon days as a programmer.
These folks are consistently the ones who make the worst decisions because they falsely believe their intuition of how software worked 20 years ago is valuable insight for technical decisions being made today.
People on the author's side of this debate just haven't seen the firsthand evidence yet. I can understand being skeptical until then, but they owe it to themselves to give late-2026 frontier models a try.
The lightbulb moment for me was when I gave Claude Code a tough reverse-engineering problem: understanding how a complex, proprietary encoding scheme worked, then building an encoder and decoder. There are some additional complicating factors that I can't disclose, because this was for work, but it was a tough problem.
For context, I've been doing RE for over 25 years. I'm not the best in the world, but I'm pretty good at it when I can find the time.
A coworker and I had spent about a week on the work, and I estimated it would take us another 2-3 to complete the work. We had figured out how about 3/4 of the messages were encoded, but the rest just didn't make sense.
I gave Claude Code our notes, and in 15 minutes it had finished figuring out the rest of the protocol and built a command-line decoder. I asked it to add an encoding feature, and in another ten minutes, it had done that as well. It tested all of its own code extensively using our corpus of real data.
The decoder worked perfectly on all of our existing captures as well as new data collected after that.
I had to make a small change to the encoder that was related to one of the things I can't disclose. I don't hold that against the model, because it didn't have access to the real product to test its output against. Making the change took maybe an hour because there was some trial-and-error involved.
That kind of capability is a genuine game-changer, especially when the interface is "describe the result you want in natural language". Ten years ago, I would have thought a truly useful natural language interface to a complex system was 20 to 30 years away at best.
Being able to quickly clone nearly all of the functionality of Adobe's entire product suite is another favourite example of mine.
This is by far the most disruptive technology I've seen introduced in my lifetime. A lot of people are using it for questionable purposes, but that always happens when people are figuring out how to make the best use of something new.
Of course if all you care about is yourself and you don't see the massive amounts of corruption, societal, and ecological harms going on, I would urge you to get your head out of the sand. You're on the chopping block like everyone else in the eyes of these corporations. If you're on the "in charge" side of things, well good luck with your moat and delusions man, legislation is coming for your business.
> I picked on Bill Gates above to illustrate the overconfidence effect
After having read your blog i can assert you've demonstrated that effect on yourself. Bill has all capability and credentials proven so we know this guy is an authority on software engineering topics, you have zero if i'm not mistaken.
Gates has made some spectacularly bad calls. He does not have any authority on software engineering topics.
I would bet his spectacularly good calls vastly outnumber his spectacularly bad calls. After stepping down as CEO, he was the chief architect and remains a technology advisor of the tech company that is currently one of the most valuable companies ever. That basically implies a long rarely-broken string of good calls. He has led software engineering at a scale only a handful of people ever have.
I would say he has more authority on software engineering topics than most people on earth, but that’s just me.
I would bet they don't.
You are just focusing on the tech bit. Bill gates never was a very good person to begin with and then he did some stuff that pretty much offset whatever good he did.
As for software engineering: if you think Bill Gates is an authority in the field I would like to introduce you to Donald Knuth, Peter Norvig, Fabrice Bellard, Dennis Ritchie, Linus Torvalds and many others. Bill Gates wouldn't make the top 100.
> Gates has made some spectacularly bad calls.
Notably hanging out with Epstein
> and credentials proven s
Gates doesn't have the biology credentials. He's a pedophile, to top it off, so most probably that's where the article should have started with. It's telling that for most of the last 30 or so years the most wealthy person on this planet has been a pedophile, come to think of it maybe we (the human species) do deserve what's coming.
Sure he does - he founded for the past decades frontier biology research. We don't have to like Gates but this discussion here isn't about that part.
Having enough capital and passing knowledge to fund research in an area and actually being an expert in an area are not the same thing.
He didn't claim to be an expert. You don't need to be an expert to come up with a question more advanced than what's on a high school test.
The article author accuses him of thinking himself an expert for that reason, I think the article author does not know what an AP exam is.
There's this thing people with strong opinions about something love to do: appeal to authority when it suites their agenda. This guy was once, a very long time ago in technical terms, very accomplished, so therefore everything he says now is more credible.
It's absolutely infuriating because it allows people with a lot of money tell you they know what they're talking about without proving it. Your money is your perceived effort, no matter how you acquired it.
https://en.wikipedia.org/wiki/Argument_from_authority
Author is spot on on Bill Gates. By his own admission, his company essentially missed the coming of the Internet, and we all literally suffer today for it.
He missed the coming interconnectedness of the machines and instead presumed that every computer was going to be a fancy copy machine calculator (that will never talk to others, thus security is not needed).
A massive hole in perception.
This is a misleading reading of history.
billg wrote the “Internet Tidal Wave” memo in May of 1995! This was an era when the dominant enterprise IT infrastructure was heavyweight (Windows!) client/server and homes were just starting to connect to the internet via dialup en masse.
Microsoft proceeded to pivot so successfully that they monopolized the web browser market alongside winning a massively profitable position in enterprise “intranet” apps and TCP/IP-based servers.
Microsoft missed mobile, not the Internet.
> his is a misleading reading of history.
The history of AOL predates this and Netscape IPO'd a few months after Gates' writing. They filled gaps that MS was obviously missing.
By May of 1995 I'd been using the Internet/DARPNET for 10 years, and learning of that memo it was like reading an old man's realization.
If Microsoft had gone all in on the Internet in 1985 instead of DOS, Windows & building a dominant app platform + office suite, no one would remember them today.
I’d say Gates’ timing was pretty good!
The first part of the article makes sense in that:
In any system of competing agents (such as human beings) where the reward for performance can enhance performance, will always result in even minor random differentials in initial performance exponentially accumulating until one or a handful of individuals dominate. In such a system, only a small portion of success can be attributed to innate skills. So it's true that success in itself, while signaling fitness to survive, does not necessarily signal an outsized ability to make accurate judgements.
I'm not entirely clear what the second part of the article is trying to convey. Is it that highly successful individuals attribute their success entirely to their skill and therefore when a machine is able to replicate their skillset, they are surprised and consider the technology to be world-altering?
What I have seen first-hand is very talented individuals in one domain (tech) assume immediate authority in a novel domain (in my case it was local city planning). The thinking seems to be sort of the human equivalent of AGI? Note how confidently Gates talks about his expertise in novel biological science, for example.
Not doubting the intelligence of these individuals, just saying they sure tend to undervalue domain specific expertise. I don't know who Elon consulted about his cybertruck, but it wasn't truck people.
I do worry that AI exasperates this problem as a quick few queries and thoughtful questions have certainly given me over-confidence in a new subject. You don't know what you don't know.
Some call this "epistemic trespassing".
It’s a fun read.
But today’s agents are “superintelligent,” the same way that trains are “superlocomotive”—that is, faster than a running human. And they can carry more. Trains are just better at getting from point A to point B than humans.
That doesn’t mean trains are a superrace and humans are obsolete, just that we’ve built machines that can do something more effectively than our bodies are physically capable of, as usual.
Intelligence isn’t what makes us human. A human who can’t play chess or write a sonnet is still a human being.
They are called “agents” because they can, and do, perform actions autonomously on our behalf. Virtual agents are not a new thing.
Programming has always been just plumbing.
Designing new algorithms is where the real skill is, but an average programmer will never do this, and even a 10x programmer will do it maybe a few times in their lifetime at most.
LLMs generate code that (often) works, but do they write "good code"? Do you find LLM-generated code intuitive, readable, or elegant?
I'm not sure I do, which is why I find it puzzling when I hear/read people saying that LLMs write better code than they can, or at least code that's just as good (re-quoting Bill Gates from the article: "I could see that they are as good as I am").
It's now possible to "vibecode" entire applications without taking a single look at the code, but that’s not what my comment is about.
LLM-generated code isn't meant to be read by humans. LLMs specialize in generating text, and they're very good at it. But what they can't do is generate text as as if it were written by a human, for a human. I get this feeling from LLM-generated code, but also from most of the LLM-generated fiction, instructions, reports, etc.
What is the opposite of the Dunning-Kruger effect? Where you believe since you don’t know anything about a topic (eg biology), therefore nobody else can (you must have some incredible decades of research experience to have novel thoughts on it)?
Spot on. I think this is referred to as “Nothing ever happens.”
Harsh, but fair.
It seems pretty clear to me that Bill was saying AI was as good as him a few months ago and now it is superhuman. This is an interview transcript, remember, not a written affidavit. Humans can switch focus mid stream.
author is trying to gate keep - yeah billg might not have studied biology in college - but through self education he might have become a master at it.
there's no law that says you can't be top in two fields at once.
Being successful is a form of being rich as enriching my hobbies, lifestyle, work profile and processes. Income doesn't need to be money to be useful.
The author is correct, although how he frames his perspective could be communicated better. Then again, that's judging his writing from a professional critique writer's opinion, this is an ordinary non-pro writer.
We have a serious problem in human society where people delude themselves routinely to believe expertise in one area magically translates to areas one has no experience. This is probably a human survival trait. It makes no sense, from a logical perspective: to venture into an area where one is educated enough to understand the danger of operating outside one's understanding is well ingrained by our educations, but we routinely ignore that like it does not exist. Perhaps this arrogance is how man's stupid will to force forward becomes our survival fitness.
The overconfidence effect is well documented and a known thing in light aircraft private aviation. People with education and good paying professional careers (doctors, lawyers, dentists, etc) who have the disposable income to buy a $300,000 aircraft and maintain it can easily become overconfident in their abilities. Because they're good at one thing in their life that requires a lot of education and training, they think it automatically extends to every other domain of knowledge that they set themselves to.
The original v-tailed Beechcraft Bonanza used to be known as the "v-tailed doctor killer".
Every IT project I've worked on for the last 25years have been successful even though usually 30% of IT project fail.
I'm smart enough to know that I can't make a distinction between my expertise or luck for the success of those project. But my ego wants it to be my expertise because I'm the only constant in those projects
There's something I find difficult when reading this piece. The thing is, I've been making a living as a programmer and I'm now in my seventh year, but programming wasn't actually my major. I majored in computational physics in university, jumped into programming on that basis, and taught myself programming. So does that mean I have no right to make up programming problems and ask questions? I mean, couldn't Bill Gates have studied biology hard and understood things outside his own field too?
Or is the theme of the piece that one ought to have epistemic humility?
But the thing is, this piece itself also makes claims about psychology, power theory, and human nature to some degree, which is ironic. But that can't be it. Because this piece has no epistemic humility in it.
Then, if we demand according to what this piece says, in the end it comes down to "no one can test AI outside the major they studied in university" — but honestly, isn't it just a matter of buying the textbooks and papers and testing AI with them?
It's a slightly difficult problem.
> does that mean I have no right to make up programming problems and ask questions?
Of course not, but that's not what's being argued. If you believed you could authoritatively declare what AI is or is not, that would be different, though.
> couldn't Bill Gates have studied biology hard and understood things outside his own field too?
Yes but he would still be a dilettante. Belief to the contrary is more likely to be an indication of engineer's disease.
To be honest with you, I don't understand why you rate this piece so highly. This piece basically shows a strong self-contradiction. If it's due to human writing having self-contradiction, then this piece would be human. If that's the case, I think AI writing is better.
The point of the matter is that the intellectual humility the author of this piece advocates isn't present in this piece. What papers are cited for the psychological claims the author of this piece makes? Of course, there's no need to do that in a blog essay. But the target of this piece's criticism is the absolutization of one's own standards and epistemic humility, and the problem is that this piece also commits that contradiction. This is a matter of the piece's level. I respect the intellectual aesthetics of people who like this kind of writing, but it's not my taste.
Well said. I don't believe the author has any credentials or accolades in psychology or sociology, but they certainly have strong opinions on how other people should form opinions.
What I am seeing in the article is an unchecked case of cognitive dissonance. That's just the overwhelming sense I get. You identified it as self-contradiction. The reason I label it cognitive dissonance is that the author is arguing against something that they themselves are projecting; that subject matter experts in one domain are overconfident in another.
This article's self-fulfilling prophecy is that it will one day be used as an argument from authority, if it hasn't already.
For sure, Bill Gates didn’t study biology for four years in college and doesn’t have diploma. How come he can now ask questions about biology after being envolved in the field for fifteen (or how many) years? Get off biology’s lawn.
Also, Dunning-Kruger effect doesn’t exist. It’s autocorrelation.
The underlying thesis is that real power should be reserved for people with philosophy degrees
Do you think aging billionaires "study things hard"? Or just talk to a lot of people and have a very surface level understanding?
These kind of people are where they are because they become completely obsessed with a topic, so I can believe he studied hard, if he was obsessed with it.
Depends on the billionaires. Some, like Gates and Buffett, are introverts who've spent a lifetime doing lots of reading. I doubt they suddenly changed their personalities upon reaching some particular net worth.
But they do get to spend as much time as they like talking with leading experts in any field. I have a hard time seeing that as a disadvantage.
Whether Bill Gates is smart or not isn't my concern. I'm someone who reads his writing often, and I think his writing is worth reading. That said, on the other hand, this piece actually does contain a performative contradiction to some degree.
The theme of this piece is, in fact, "don't absolutize your own standards" — that successful people forget the contingency of their success, forget the situation and context of their judgment, and treat it as a universally correct judgment. But the problem lies in the writing itself that carries this piece's theme.
A doctor can smoke while telling a patient that smoking is bad — that's not a problem at all. The biggest contradiction in this piece is that, while warning against "absolutizing one's own standards outside one's own field," it reinforced the psychological parts without any argument or evidence. Honestly, everyone has that degree of contradiction in a homepage essay. So do I.
But separate from that, the difficulty in reading this piece is that if you're going to demand intellectual humility, you should at least be consistent within the text. You can criticize the act of reinforcing one's own standards outside one's field. The problem is that it's hard when, within the text, the author violates the very standards he set. I also tend to think this is to some degree a general human trait. Everyone has some logical leaps... it's not a bad thing, but that's how I am.
There’s no reason they can’t. To be honest, it seems to me that the author hasn’t studied hard here; I can’t imagine anyone being so dismissive if they have detailed personal experience of what the current crop of frontier models can do on whatever kind of intellectual task they feel is important.
At the end this repeats that AI has reversed huge reductions in CO2 emissions. I keep seeing this. Is this chart wrong?
https://ourworldindata.org/profile/co2/united-states
The second chart is the one I’m looking at. Where is the 15 year reversal? If zoom in I see a small uptick. Not a 15 year trend reversal.
It’s just plainly not true. Yes AI uses electricity but it’s not that large a percentage of global electricity use. A lot has been happening globally that effects energy use the last few years.
I also tend to blame any uptick on electing a president that explicitly ran on burning more coal and spent money to subsidize keeping otherwise obsolete coal online.
I keep hearing this AI water and energy panic stuff. I’m a believer in facts, so I go looking for it, and it’s just not there. Water use is similar to golf courses and light agriculture, though I can see it being a problem in places like the Southwest. The electricity use is decent but not at the levels people are losing their minds over.
It’s just not there.
I can see some of the complaints over noise and political corruption like special tax breaks and deals.
US coal use peaked in 2007 and only had a small uptick in 2025 mostly down to demand for electricity outstripping the ability to build new supply. It had little to do with current administration policy. In other circumstances the coal plants that went back online may have been converted to natural gas but it’s hard to say what then counter factual would have been.
It links to a source
https://www.bloomberg.com/news/articles/2026-10-28/us-data-c...
Yeah, it's still not true.
The 15 years is a projection based on data center build outs and gas turbine generators like those Collosus uses.
Hyperscalers want to build out enough that the trend will reverse. How much is t.b.d., America is likely to slow down the buildout
I note that that chart doesn't contain data for 2026. It also doesn't contain data for 2030.
Unless something catastrophic happens, [0] construction four years out is effectively locked in. When what's being constructed is expected to increase CO2 emissions by ~50% after it's built, it's quite reasonable to assert that the LLM Industry has reversed our collective work on cutting CO2 emissions. It's exceedingly reasonable to bitch bitterly about it when those very same entities driving the construction today were screaming left and right about all of the initiatives they'd been championing to reduce power consumption and Save The Planet and whatnot just a few years ago.
[0] ..such as a fuckoff-huge bubble that's being used to justify said construction messily exploding...
The construction plans are nuts and it looks very much like a real estate bubble. I will be shocked if more than 1/4 of that gets built.
Chip efficiency gains will mean that by 2030 you’ll be getting 100X the inference throughput on half the power. All this construction is not necessary.
> The construction plans are nuts...
They're in line with what's needed to meet the revenue projections of the LLM companies. Your "100x the inference" assertion ignores the most expensive part of the work of creating SOTA LLMs... the "training". That is what the DCs are primarily being built to do.
Jeven's Paradox means chip effeciency will be moot. It's about footprint and macro measures
Depends on how big the efficiency gains are. There is not infinite demand. Jevon’s paradox occurs when there is latent demand that is released at a lower price point.
I also found that these projections are 15 years ahead and assume nearly all power is from gas when battery and solar costs are still falling geometrically and data center demand has reignited modular nuclear interest.
I’m generally skeptical of all predictions of the form “look at this terrifying thing that happens if we extrapolate the current trends indefinitely!” See: “The Population Bomb” by Paul Erlich and countless other doom predictions of a similar nature.
Not being Pollyanna either. Just being realistic.
Some things that have thrown all CO2 / gas projections off are
1. Trump's War
2. Falling birth rates
3. Petro vs Electro state directions (Russia -> US -> China)
There are also unknowns around the thawing of the permafrost at northern latitudes.
Yeah my biggest concern is we have already tipped the climate and it’s currently ratcheting up to the next stable slot… one where we maybe lose Miami and experience huge agricultural region shifts that will destabilize governments and societies.
But hey. FAFO. We will live and adapt. Humans are like cockroaches, as a bio professor said to me once, and he explained that this is not an insult.
The difference here that it does actually make us gods. Kinda.
Is the title a reference to Richard Dawkins' The God Delusion? Seems too punny not to be.
This piece reads very much like the conclusion was arrived at before any of the evidence, and even though the arguments were flimsy that didn’t stop the author from including them. Gee, I guess they’re unqualified to have an opinion on this topic and should just shut their mouth and let someone with a Ph.D. speak.
None of this matters. By the time truth out itself, the Kushner's, Gate's, Andreeson's, and Altman's of the world will have walked off with hundred of billions of our 401k money.
No one is forcing you to invest in anything
It is possible to have a healthy society without billionaires.
Is it?
yes
The index makers are. And the coming bailout will.
You are not compelled to invest in any indices. Pretty much all 401k plans have bond options. Even better, you can also go ahead and short as many AI companies as you want if you are so confident you have market-beating insight and join in on these supposed billions that are free for the taking. But I know, it’s a little harder to put your money where your mouth is than to put your mouth where the karma is.
You can also just not participate in the 401k program altogether.
Money gets a lot simpler when it's on cash basis in an ordinary bank.
A 401k is not a magical guarantee that your retirement will go well.
These people are going to be so cruel and vindictive when they are finally forced to look up. Not looking forward to it :(
Older posts on this site seem to have been interesting but the author is ultimately now captured by some distaste for AI and can no longer produce useful text.
* The Claude Delusion (2026-11-13)
* This is not sustainable (2026-10-27)
* 'Winning AI' (2026-10-01)
* Everybody's Lost Their Minds (2026-09-16)
Definitely a trap I need to keep in mind as I blog since I don’t want to become like that.
They are more inline with where society outside of tech is. Outside our bubble, people are very angry at tech bros, and we face a reckoning. These are in a way and attempt self critique and persuasion. I have one in the works as well
> or a share of an emerald mine from their fathers
This is so lazy and petty it made me stop reading. Whatever you think of Musk, it's trivially verifiable that the emerald mine thing is a myth.
And in case you think I'm some evil right-wing troll, here's the LA Times telling you the same thing:
> Over the years, Musk critics have accused him of getting a leg up in life because of money his father made from emerald mines. Isaacson, who interviewed Errol Musk, reports that Errol struck a black-market deal to receive emeralds from three mines in Zambia to cut in Johannesburg, but that Errol did not have an ownership stake in the mines. He reportedly earned $210,000 from those mines before the business collapsed in the 1980s.
> But Isaacson calls it a “myth” that Elon emigrated in 1989 with wealth from his father’s emerald business. Isaacson writes that Errol’s emerald business had become “worthless” years earlier, and that he only gave his son $2,000 in traveler’s checks when Elon Musk moved to Canada that year.
I mean...really. The LA Times hates reporting this so much that they put idiotic scare quotes around the words "myth" and "worthless", but they still have to print it, because it comes directly from one of the eminent biographers in the world today, who interviewed Musk's father.
https://www.latimes.com/entertainment-arts/books/story/2023-...
> Anything approaching my skill level is superhuman
Or someone has the impression that Ai can code as well as them (and find errors) but at 10x the speed or more. They then conclude that human ability and superhuman speed is superhuman in total.
There is a documentary called Chimp Empire that follows societies of Chimpanzés in Uganda. You can see very nicely which human proclivities come from primate architecture. Social ladders to the extreme, bullying, nepotism, signalling, trust and alliances, tribe wars, survival, the alphas who get to produce a bunch of offspring but almost always die young from opponent beatings. Intelligence is everywhere and the patterns it has are everywhere. One Chimp finds a good new edible thing or tool to eat new edible things and the whole tribe learns about it, and everyone eats better. One chimp gets a new poisonous mushroom and tells others by dying - the others may even evolve to use the mushroom to hunt. The more chimps you have out there the more have to feed and hunt and find new tricks and if there are tricks to be found - great. If there aren’t, eventually the larger group goes against other chimp groups to get their foods the violent way.
You can look at this article like a chimp who envies on an alpha while having “Meister” in his domain name. You can look at it as descent to a group of chimps that have gone to pluck a field of toxic mushrooms.
When you look above the primate behaviors, the only question that matters is not if the new stick invented is better than having more chimps, but if the new stick will be used to grow the chimp universe or to shrink the # of chimps in the universe so one tribe gets the universe - under the premise of “all those chimps are ruining my universe”. It’s not whether it’s smarter or more powerful, but how its used. The confident will try more things than the doubtful. The scared will try less - will the stick be used to scare you into not trying?
If we had to actually be responsible and care about people or the world around us, we couldn't make these models as good as they are. Humanity needs this and they just don't understand. They'll understand when my ${insert-company-name} innovates on this ${insert-anti-human-bullshit-idea} for the betterment of mankind. The jobs? Nobody needs jobs and caring about that doesn't make me money. Security? Yeah, the industry has known how to do isolation for decades, but that takes away from the hundreds of billions of dollars to buy compute. We could avoid massive economic impact if we just wait for the electrical grid to catch up to power our datacenters? Nah, we care about money more than people or the environment.
It's all so short sighted and anyone supporting this behavior is anti-humanity.
Tendency to express overly confident opinions on every field possible is shared in many professional subcultures, including for instance, journalists, and philosophy graduates. And the last category is rarely successful in conventional sense. After you learned to measure your self-worth on a particular scale (intelligence in this case) you naturally will try to persuade everyone, and yourself in the first turn, that you are not worthless. So within the modern society as it is, it's natural bias for all nerds, whether we into tech, biz, or humanities. It just that if you happened to be rich and famous then you are more visible, and bloggers will judge exactly your overconfidence, and if you are a red-shirt peasant - you can't draw enough attention, and will be judged by your spouse.
This is a great journey through a biased, stereotyping mind.
> biased, stereotyping mind
That's just being human. If we step outside the tech echo chamber, many many people feel this way towards "tech bros." Do or don't be surprised when they give us a comeuppance.
Feelings are not rational. The reflexive "tech bros" is the result of a lot of indoctrination.
> The reflexive "tech bros" is the result of
Seeing the ultra wealth playboys who brought them addictive technology and are automating away their jobs.
Calling it indoctrination is a fallacy. Talking with non-tech people about these things will uncover as much.
> Calling it indoctrination is a fallacy. Talking with non-tech people about these things will uncover as much.
The only fallacy is your implied claim that if non-technical people think it then it can't be indoctrination.
Do you really believe the majority of people are indoctrinated and have no valid thoughts or feelings on these things?
If yes, what about you, compared to them, makes you immune to indoctrination?
My main counterpoint datum is the US midterm election exit polls. People said affordability and corruption are their top issues and that they are interconnected. Tech bros are their exemplar de jour - with good reason.
> Do you really believe the majority of people are indoctrinated and have no valid thoughts or feelings on these things?
If half the population consume the same sort of media that's all saying the same thing then they're very likely to believe the same thing. They will believe they noticed something, when in fact they were told it over and over. Pick whichever half you like. Just as I don't trust a nationalist's opinion on immigration, I don't trust a Marxist's opinion on the wealthy.
As for "valid feelings" I agree this is about feelings and not thoughts, but I don't know what a valid or invalid feeling is.
> If half the population consume the same sort of media that's all saying the same thing then they're very likely to believe the same thing.
The naivety... to assume people agree with or support everything they read or watch. How are we to know what others think without consuming their content? How are we to persuade them of weak points in their arguments if we do not know the foundations?
What indoctrination have you yourself been subjected to? You seem to be stuck on a bipolar view, defined by the extremes (a minority), in a nuanced world that is growing increasingly tired of the extremes, their reductionist perspectives, and their bickering.
My favourite diss for all overconfident programmers is, if all these people are so brilliant why does so much software suck? But yes anyone thrust into the spotlight tends to think they’re the cat’s pyjamas.
So... engineering and hard technical work are associated with higher intelligence.
And being more intelligent than average makes you...by definition superior at being intelligent.
Also Bill Gates is highly intelligent, rich, and successful, so... 'more superior' by definition than 99% of us (Yep me too).
And I guess the author also has some sense of superiority, because I'd certainly be too embarrassed to post this anywhere if I wrote this shit.
As usual with posts like these, this is someone trying to turn their emotions into logic.
same thing also happens all over the comments to these posts, and to me reinforces the core message of this post
This guy 100% loves to read his own writing.
Many comments struggle on the "superhuman" claim.
Being "human" is ill-defined. Being "super-human" even more. LLMs abilities are superior to humans in many ways, sure. So does my calculator. So does an excavator.
LLMs are "super-humans" in novel ways, sure. But machines having superior abilities than humans' is nothing new. Nothing.
Can we move on and make something good now?
This is the exact kind of article I find deeply self-important and pretentiously delusional, ironically enough.
Sure, the biology point is fair. The rest is very silly. It moving on to say Bill Gates is therefore wrong to fear the pace of AI improvement is extremely silly.
> This narrative of agency conveniently also relieves you of responsibility. You didn't fail to properly restrict a potentially malicious program you trained to hack other systems with persistence. No, the "agents" went "rogue".
This will be the thing that really hurts the frontier labs. I believe they will be sued into oblivion and regulated in surprising ways.
"the very notion that something else could be "as good as I am" is, first of all, hard to believe and secondly necessarily means that it's "superhuman". That man is not lacking self-esteem, no sirree, Bob. "
I like that the article just tries to pass off a computer program coding at the level of humans (not to mention solving Millennium Problems) as something that should be just be totally unsurprising. Bill Gates is just a dumb arrogant tech bro to be surprised that a neural network exceeds his abilities at coding.
I'm trying to find the exact clip, but there's a segment of an interview where Elon Musk explains why he finds it likely that we are living in a simulation, and part of his evidence is how unlikely he finds it to be him: He's the richest man in the world, the first trillionaire, he's influencing geopolitics and launching space rockets.
He finds it so astounding to be himself, to feel like the Main Character of the World that he considers this evidence that the world he experiences is a simulation. The more humbling proposition -- that the world is largely random and he just happens to be the guy who kept rolling sixes -- is less compelling.
Edit: I think this is the clip I was remembering https://x.com/firesidealpha/status/2112531407390343670 but he's said similar things in other venues.
Dw im picking up what you’re putting down
related: Why 'Merit' Should Be Rejected
https://www.youtube.com/watch?v=Vp5qsEuUOWo
Same idea, more general and eloquent
I want to preface what I'm about to say with the fact that I believe super intelligence is (by some reasonable definition) more likely than not to arrive some time next year.
However, today's models have extremely jagged intelligence even within fields they're extremely capable in.
Like most people here, I use Claude and other models daily and I used them primarily in the context of building a very complex software project. Claude is brilliant at writing code at, in very clean and well defined codebases, where its being asked to build something that fits well within the preexisting patterns.
Someone non-technical who does a lot of vibe coding recently asked why I couldn't just tell Claude to go build some feature into the project and call it a day? And it's genuinely hard to explain to people who are not both experts broadly in the field and experts in the specifics of the problem why this such a bad idea. And annoyingly it's not that Claude won't produce something that works, it will produce something that makes several extremely bad assumptions and defensively codes in those assumptions. And even when you explain this, the question then changes to, "yeah, but you could just ask Claude to fix that".
My default way of working today is to start 90% of my projects by simply asking in a few paragraphs what I want, seeing what Claude builds then spending half a day working through it, explaining all the wrong assumptions it's made, then reaching a clean and maintainable solution at the end.
However, I have been on the other side of this and I've felt magic of Claude when I've got it to write code I don't really understand. On the surface it seems to be able to do everything I ask stupidly fast. It's better than any human you could ever work with. But who knows what it's doing under the hood... My guess is that you simply can't keep building like that for long because while it will do everything you ask, the foundations of what it's building on are basically non-existent – and anyone whose worked on a serious software project before knows the foundations of any software are by far the most important things in the long-term robustness and maintainability of the project.
I guess what I'm saying is that many people who are non-experts in the field or non-exports in the specific problem within the fields they're asking AI to do things are largely delusional about what AI can and can't do. It absolutely can create a simple CRUD app, but it will not build a complicated distributed system and process millions of requests a day with five 9s of uptime.
That's not to say it will never happen. I think it will, but there's some things that need to be figured out first.
I was working with someone earlier this week who was telling me about how he convinced GPT-6.1 his name was an an XSS attack string. I don't think you could convince 1 in a million humans that your legal name is genuinely <script>alert("hello!");</script> and yet these models are supposed to be experts in domains like cyber security and super intelligent? It's honestly staggering how stupid they can be whilst also being so competent at a surface level.
This article articulates several thoughts I share with the author well. If there is anything people in the technology industry lack, it's intellectual humility.
That, and, they are pitifully ahistorical people. Today's industry leaders are not sufficiently schooled in constructivism. No, I don't mean they all need to become radical constructivists, but they should all at least gain a passing familiarity with Foucault before they continue fucking with humanity's social mores and environments with impunity.
They won't, of course, because they are decidedly unreflective (see Andreessen), unphilosophical people. They are, oftentimes, the marquee examples of 'soulless' people fueled only by the incentive structures put before them by the economy. Money. Clout. "Progress". It's telling that, beyond the many examples of hubris like that of Gates, basically zero technologists have come out and examined the unspoken assumptions behind such terms as "progress", "alignment", "intelligence" and the difficult social problems fixing these terms would entail. Moreover, they interpret all of these terms using some reified capitalistic gloss and go on their merry way, because, in spite of their constant proclamations to the contrary, most of them are not, in fact, very intelligent beyond being savvy businessmen.
The employees bear the brunt of actual technical intelligence. Leadership bears little more than a passing ability to navigate an economic structure that, let's face it, is already very forgiving to them and essentially places little to no responsibility on them after certain levels of scale are achieved. But none of that scale is possible without the vast legions of employees. Oftentimes the 'genius idea' is about 0.5% of the actual success of an endeavor, yet we cling to an old "great men of history" form of thinking and allow the public to prop up these individuals as though they are demigods.
Writing like this is corrosive. The most effective takeaway that it contains (about overconfidence) is banal. Everything else is an aggrieved deconstruction of—out of all things—a conversation between Ezra Klein and Bill Gates for the New York Times.
The true integrity and value of this blog post depends on your own interpretation of the author's interpretation of the hour-long podcast plus his supporting snipes toward Gates, Musk, Trump and other Tech Bros (read: Bad Nerds).
As an appendix I want to link to this submission from 3 months ago:
https://news.ycombinator.com/item?id=49160437
> snipes toward Gates, Musk, Trump and other Tech Bros (read: Bad Nerds).
It's where broader society is at, like it or not. They are angry at the "coastal elites" which now includes the tech sector.
> They are angry at the "coastal elites"
Ugh. You're right. And I'm not surprised to see these sort of complaints coming from the opposite side.
> from the opposite side
It's coming from both sides now. The political bipolarization fever may have broken in the US. The growing division is between haves and have nots.
Perhaps they are right and we are not https://www.youtube.com/watch?v=Vp5qsEuUOWo
Ah yes, the professor from Hoboken is here to teach us that tech bros are delusional, and it’s really professors from Hoboken who know what is actually going on.
Biases and heuristics have become somewhat mainstream “intellectualism”, but just like people using the words prolific and myriad incorrectly, is leveraged here to a false conclusion.
The anti-AI narrative continues, to the detriment of those who listen to its self-destructive guidance that equates excessive enthusiasm with delusion.
Both the author's and your perspectives can be wrong at the same time, yet have elements of truth. Certainly the phrase "coastal elites" did not come from nothing. At the same time, the critiques have their own form of intellectual elitism, in essence doing the same thing they critique.
> The anti-AI narrative continues, to the detriment of those who listen to its self-destructive guidance
Can you expand on your view of the narrative (which one) and why it is self-destructive (which one)?
The narrative of AI being of illusory value, only appealing to the delusional tech elite, is one that serves only to soothe the emotions of those who are unwilling to embrace reality.
The technology is useful (while imperfect)
That's not the narrative that I read in the post. It was people who excel in on area believing their expertise translates to other things. The leaders of Ai are doing this
he presents the idea of Bill Gates observing an OpenAI model a. doing "complex" biology problems, b. some coding problems, and then based on his assumption that Bill Gates knows rudimentary biology, and used to also write code, the fact that Bill Gates is impressed with the OpenAI model means Bill Gates thinks he has superhuman biology and coding skills. This simply does not follow.
This would be like if I went in my garage, spent several weeks with the 3d printer and CNC machine to build a robot that can "dance", then I made a video of me dancing about as well as your average dad at a wedding along with my dancing robot and I said "this thing can dance better than me!", therefore: "Ha, your robot sucks! You must think you're Baryshnikov if you call that dancing". I mean this is kind of sad.
Slightly more than a couple of years ago, just observing an LLM coherently doing work at the academic level of a sixth grader was brand new to all of us. Which was objectively impressive. It doesnt matter "so what? anyone can do 6th grade math"....this..is not..the point...
edit: the point they want to make, that these people are not qualified to make dire predictions about "superintelligence", and that they see themselves fit to determine "superintelligence" based on watching the robots be smarter than them, is one I generally agree with, and their certainty originates from a kind of hubris. but it's not a hubris you can assign to the general LLM-using population as this seems to be doing. Most people using LLMs think the "superintelligence" thing is a load of bunk (probably moreso than the general population who seem to be cowering in terror).
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I am no fan of Bill Gates. He's pedophile adjacent, in my *opinion.
But I was there. He worked really, really fucking hard. As did most of the early crowd. If you're asking yourself how people back then worked so hard, just realize that there are drugs that can help you do that.