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Why I'm still bearish on LLMs after Navier-Stokes

dank.systems

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Re: Why I'm still bearish on LLMs after Navier-Stokes

#611

Post by keeda »

danpalmer wrote: post #358
keeda wrote: post #73

The premise in the very first point seems off: > the frontier labs are priced according to the narrative that they have produced or will in the very near future produce a fully automated drop-in replacement for most knowledge workers... Even assuming this is how the AI companies are being valued (they're not), the numbers are off. The "value" of most knowledge workers -- based on what enterprises currently pay for th…

> It's reasonable to assume that if AI drop-in-replaced all those knowledge workers, AI companies could credibly charge somewhere in that order of magnitude, because that's what the market is already bearing This assumes you don't change the market, but at the scale of (checks notes...) "all knowledge work", that just doesn't hold. For example if you put 1bn people out of work, you now need some sort of safety net to…

Yes, posted it elsewhere: https://news.ycombinator.com/item?id=49722616 -- this is necessarily a simplistic analysis to address a simplistic point in TFA, but it still kinda-sorta works assuming AI only augments workers and does not replace them wholesale.

However, I fear reality will be much hairier.

Re: Why I'm still bearish on LLMs after Navier-Stokes

#612

Post by [deleted] »

randomImmigrant wrote: post #471
handfuloflight wrote: post #67

Earlier quoted context omitted.

> This plus the memory issues make dreams of long horizon agents, that could plausibly handle changing specifications, quite implausible with current architectures. Any reason why that can't be solved through context management and keep-forward scaffolding?

And who’s to manage context? And who’s building the scaffolding? Yes, AI can be used for both, but you do realize that all this being self-contained and regulated internally is what makes biological agents successful agents, right? If you break the process apart and need to dial back in these aspects, and can only do so with human input, or another agent which will need the same handholding the one whose issues you’r…

[deleted]

Re: Why I'm still bearish on LLMs after Navier-Stokes

#613

Post by miguelacevedo »

> the difference is that the data center full of geniuses is self-driving and limited only by how much compute it can consume while the brainlet swarms will be heavily bottlenecked by their human orchestrators.

Here's another human bottleneck: "AI Has a Discovery Problem" (https://news.ycombinator.com/item?id=49621223)

Re: Why I'm still bearish on LLMs after Navier-Stokes

#614

Post by numitus »

senordevnyc wrote: post #595
numitus wrote: post #544

Earlier quoted context omitted.

Tests are often conducted under restricted conditions. For example, elementary school students aren't given calculators in math class, or during an interview, you are asked what encapsulation is and aren't allowed to use Google. The chess test effectively demonstrates the reasoning capabilities of an LLM without relying on brute force, because a human is incapable of calculating trillions of combinations yet plays ch…

People might care about this for chess, but no one really cares if an LLM can command an army or manage production of a business without any tools. If it can do those tasks reliably when given access to tools (including any tools it autonomously creates for itself), then that's more than sufficient. No one cares if an LLM is doing reasoning the way humans do it, as long as it can get the job done.

The assumption is that if an LLM is incapable of playing chess—a game with a relatively small number of pieces, clear and simple rules, and perfect information—even after reading a hundred thousand books on chess, then it is fundamentally incapable of managing an army or a factory. This is because those scenarios involve more 'pieces,' incomplete and fuzzy information, and implicit rules that need to be deduced independently. It doesn't matter whether it has tools or not. It's simply that running tests with chess is cheap, whereas testing with an army or writing a browser from scratch is quite time-consuming and expensive.

Re: Why I'm still bearish on LLMs after Navier-Stokes

#615

Post by shric »

fahrvrgnugen wrote: post #218
traes wrote: post #105

Earlier quoted context omitted.

This is true, but I'm not sure it matters? I was poking around at the lichess database recently and those elo calibrated bots are remarkably well calibrated, their rating variance sticks out like a sore thumb compared to human players even at similar game volumes. So it should still be a decent predictor of how good a human at that level is, even if the playstyle seems alien.

I feel like every position is in the database so you could just lookup the most popular move for an arbitrary elo and that's the bot.

That would only work for the first few (from around 10 to 20 typically depending on how close people stick to opening book) moves.

Conservatively there are well over 10 to the 30 positions likely to show up in realistic games.

There are of the order of 10 to the 10 or so games recorded.

Thus well under one in a trillion positions are "known".

Re: Why I'm still bearish on LLMs after Navier-Stokes

#616

Post by zug_zug »

keeda wrote: post #608
zug_zug wrote: post #453

Earlier quoted context omitted.

You said 10s of trillions of dollars of revenue, which when the sum of all salaries is 65T, is minimum 15.3% of all salaries best case. It really feels like you're just pulling numbers out of nowhere here.

Yes, say the sum of all salaries paid be employers is $65T, and if AI accelerates workers by 15.4% -- studies and survey data actually suggest it's closer to 33% already e.g. https://www.stlouisfed.org/on-the-economy/2025/nov/state-gen... -- that is worth 15.4% of 65T which is 10T, which is already "double-digit trillions" as I said. Assuming a 33% boost takes it to ~20T annually, which is technically "10s of trillio…

Did you read your link? It says that 33% of people adopt AI, not that AI makes all workers 33% more effective, that would be absolutely insane. For that to be true we'd expect to see either companies who use it have revenues all suddenly jumping 33% (which we have not seen) or laying off 33% of their staff (which we have not seen and would also be catastrophic in the short term at least).

I'm not really going to belabor this point more, because it really sounds to me like you haven't even done the most cursory exploration into this and the people who have give an estimate of 7-10%[1] (and only a small fraction of that value would be captured by the AI provider). All the best.

[1] https://www.goldmansachs.com/insights/articles/generative-ai...

Re: Why I'm still bearish on LLMs after Navier-Stokes

#617

Post by nl »

lukewarm707 wrote: post #370
nl wrote: post #272

Earlier quoted context omitted.

> if that's false, anthropic is dishonest. why trust a dishonest company to be worth anything? This logic doesn't follow at all. If their argument is that there is 10% chance of extinction then they also believe there is a 90% chance it won't.

recalling the exact phrasing, several senior people at anthropic made public statements agreeing a 10% chance of causing extinction in less than 10 years. 10% is uninsurable, priced in with ordinary treatment of risk it suggests that anthropic should be worth zero today. creating that risk would put every executive in jail. on top of that it would demand under existing laws of conflict, a military campaign to destroy…

> it's not true that ai has a 10% chance of causing human extinction within 10 years.

I agree with this.

The rest of it I don't. For external actions to be taken there needs to be a consensus and there clearly isn't that.

And this sort of thing happens all the time. For example Zuckerburg thought Facebook was worth more than the $1B Yahoo offered him and he was right even though no one else agreed. He though the metaverse was worth the $20B+ they spent on it and he was wrong.

There's a gap between people thinking something within a company and people external to the company agreeing with it.

Re: Why I'm still bearish on LLMs after Navier-Stokes

#618

Post by suzzer99 »

yunwal wrote: post #606
suzzer99 wrote: post #488

Earlier quoted context omitted.

It's repetitive and controlled if you don't care about the outcome, which monopoly companies don't.

sure, but then why be bearish on LLMs? You don't even need to care about the code just check the boxes.

I assume because the market for crappy customer service isn't big enough to justify current AI company valuations.

Re: Why I'm still bearish on LLMs after Navier-Stokes

#619

Post by danpalmer »

mackeye wrote: post #377
danpalmer wrote: post #354

Earlier quoted context omitted.

It's a tech bro thing. Altman does it too, and I've worked with people in the past who do it. I read it as "I'll take literally any conscience for myself no matter how minor, at any cost for you no matter how big".

why take the least charitable possible reading D; i've always read and intended it as inviting informality. i also don't find it harder to read at all (most people don't know some find it harder to read: i didn't)

I don't read it as informal. Childish or lazy perhaps, at best.

When you intend it as "inviting informality", you're implicitly doing this because "formality" is too much effort. The thing is you're not inviting, but rather demanding. You have decided the conversation is informal and low effort, and that's how you'll treat it, without considering the person you're communicating with.

This is of course all a lot of strong statements and these things don't matter as much as this sounds. I don't feel _that_ strongly about these things, but the lowercase thing always strikes me as just plain weird, and deconstructing why I feel that way this is where I get to.

Re: Why I'm still bearish on LLMs after Navier-Stokes

#620

Post by bluegatty »

Zambyte wrote: post #374
bluegatty wrote: post #114

"are priced according to the narrative that they have produced or will in the very near future produce a fully automated drop-in replacement for most knowledge workers, " No, they're really not. They're priced in a way that would imply AI will be universal form of compute, alongside traditional deterministic systems - which it will be. And that they will capture most of that ... which they won't. The Frontier Labs ar…

Traditional non-chaotic systems* LLMs are deterministic. They are chaotic, which people confuse for non-deterministic.

I see your point but, from a systems perspective they are pragmatically non-deterministic.

The use of LLM in any system creates non-determinism in any practical sense.

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