Yeah. Sometimes I wonder who the long term financial winners will be from the ai boom. It might be ram / gpu manufacturers. Or whoever cracks putting LLMs on asics.
When the Industrial Revolution came along it did create 'super farms' relative to the past through increased efficiency and production, but it also created a huge vacuum in the economy that was ultimately filled by industry, to the point that farming, super or not, became a vanishingly small part of the overall economy - even as production continued to increase.
---
LLMs stand to do the same thing for software. If and when we reach the point of 'normal' people being able to reliably compose ultra customized software solutions to their problems, then software is basically done as a problem-solving industry in and of itself. Not 'done' as in dead, but 'done' as in solved. There's just nowhere to really go from there.
And so I think this will do the exact same thing as the Industrial Revolution did to farming and create a vacuum opening the door to all sorts of new interesting expansions in the real world, as opposed to the digital one. I don't know what this means, because it's quite difficult to foresee the impact of the Industrial Revolution when living in agrarian world, but it's not so hard to see that the future will not be agrarian.
---
So it's probably still myopic but my bet would be on the first major manufacturer of cheap customer/enterprise grade generalized robotics hardware shells.
And there I think the winner would be China.
By my reckoning, there's a significant chance most software engineers will be unemployable within a few years. But I'm not 100% confident that there'll be a utopia waiting for us, as an alternative.
Individuals can still get unlucky. Just like a coal miner might be out of a job, when solar panels become effectively free.
Software engineers are a pretty small part of the general population. And they can move into general white collar work afterwards. Perhaps at a drop in pay compared to software engineering, but still pretty cushy by the standards of ordinary people.
(And if we manage to automate all white collar work to be done cheaply and reliably by machines, well, then we are in utopia.)
So my new pet theory is that this is one of the few times we're seeing a positive effect from the heads of all of these big businesses being part of weird public (e.g. WEF) and private (e.g. Bohemian Club) orgs where they get to together and conspire to conquer the world or whatever. Rapid replacement of labor would be horrifically self defeating, because you'd end up not only tanking your own economy but having a bunch of angry and increasingly desperate people with a whole lot of time on their hands. That doesn't tend to end well for the powers that be.
So I think there's going to be a conscious effort to transition between this era, and whatever comes next, in a more controlled way than $$$ YOLO $$$.
I doubt that conspiracy theory.
I think the only assumption that's meaningfully debatable is whether the current SOTA are able to supplant labor to a more significant degree or not. And while I suppose that's going to inextricably remain an opinion, I think it's reasonably objective to say that hallucination rates have sharply declined, and overall code quality/coherence is sharply up.
Sorry to cut you off, but have you looked at Nvidia's numbers since the NFT craze? They won.
Sell shovels in a gold rush, make better shovels, repeat on the next rush.
So, my plan would be to invest not in the AI companies, but in the economy as a whole who get to use the AI for their businesses.
Caution though, one thing which AI is already superhuman at is persuasion. Regulatory capture is likely even easier today than one might expect purely from the revenues of the AI companies.
Just like Wikipedia put classic encyclopedias out of business, but wasn't really a financially win for anyone.
And it would show up in real GDP, not necessarily in nominal GDP.
What makes you think if one or two AI labs can do this that the rest (including open model providers) won't be able to follow the same path a few weeks/months later?
Even if you believe in the "Singularity", and believe it is coming soon, I still don't see any reason to believe the Singularity will be... singular. There won't be one clear winner, the race doesn't get called as soon as the first person crosses the line.
None of the AI labs are showing any sign of pulling away to a monopoly or duopoly position, to the contrary the early large leads of OpenAI and Anthropic have all been evaporating.
AI has clear economic value. It still isn't clear at all how the providers of AI will capture that value in a moatless environment with the technology becoming rapidly commoditized.
everything would have to be kept under wraps, and you'd need to avoid the scrutiny of the US gov (they already wanna eval SOTA models in advance)
I don't get this idea that "AGI" will just manipulate everyone somehow into destroying the world or something
If "human brains become fully irrelevant economically" then that brings into question the entire premise of "share holders" and "financial winners".
What even are money, shares, stocks, and finance in a world where human brains are irrelevant economically? No one knows, but betting that "share holders" will be the winners is a highly questionable bet.
I would much more likely bet that "the armed group who manages to control and benefit from the AI through force" will be the "financial winners" more so than "share holders", who tend to not be terribly military minded at least in America.
If that fails, who knows what things will look like.
If the AI gets as powerful as you think it might, then the group that figures out the answer to that would have the power, I suppose. or maybe the AI does not listen to any of them and does its own thing. Who knows? Personally, I would not bet the share holders are going to come out "on top" whatever that means.
I think a lot of share holders are finance people, not deeply technical AI people and so odds are the share holders will not really understand the AI enough to be the most likely to control the AI.
(I think it would be a good thing for humanity if they did)
- LLMs have better long term memory (they know more than any human) and more working memory (LLMs have fast, uniform access to their whole context window).
- LLMs are faster than we are.
- Humans have online learning (we can do simultaneous learning and inference), giving us advantages in many novel tasks.
- We can learn concepts from far less data. And we can manage our mental context more smoothly.
- We seem to have better world models than current models. AI video just doesn't look right, somehow.
I expect that these remaining weaknesses can be overcome without resorting to human brain emulation. I see no reason to think that current LLMs are at the limit of what technology is capable of.
For example, it seems that even at Fable scale, simple concepts like the passage of time or (gasp) timezones elude them. I live in UTC+10 and with any RFC8339 data LLMs are constantly confused - is it Sunday the 10th or Sunday the 9th, etc. I have tried many solutions for this and every time it finds a way to get it wrong.
Getting confused about timezones does not place LLMs behind that many humans. (But doing so repeatedly does highlight the lack of online learning).
How do you square that then? They can do amazing things, but they're also not smart? Do you think its possible to solve Erdos problems without any "smarts"? Can you do it without even understanding mathematics?
I find it very hard to hold the idea that LLMs don't understand anything. They can explain concepts, translate them, simplify them and implement them in code. From the outside, LLMs seem to understands most concepts better than most humans do. Do you understand anything? Couldn't I make the same argument? How would you prove that you understand what a for loop is, or that you know what calculus is? I assume you'd demonstrate your knowledge by using a for loop in a program, or explain calculus back to me. But LLMs can do that too.
> For example, it seems that even at Fable scale, simple concepts like the passage of time or (gasp) timezones elude them.
Funny example, because lots of human struggle with this too. The number of meetings I've had with people in the US! "Lets meet on thursday morning australia time!". Only, they actually meant thursday night US time, which is friday morning australia time. "Oooh that's so weird! Its the next day for you!". ...... Yes, I know.
I think LLMs are just a different kind of intelligence than humans. They're better at some things than us, and worse than others. They can find latent security vulnerabilities in the linux kernel, but struggle to count the Rs in strawberry. They're not as smart as humans in many ways. But we're not as smart as LLMs in plenty of ways too. I didn't find those linux bugs.
Are you making a serious argument that it's not?
Because you'll need to explain leading-edge mathematics advances that have come from LLMs, among other things.
Also, you may have noticed in passing that humans aren't getting any smarter, while AI models are.
That's not all of what we are doing for at least a year, possibly few. LLMs are trained increasingly on generated inputs. Soon human sourced material is going to be rounding error in the process of training.
If you add two random numbers and calculate the result and those happened to be numbers noone else ever had idea to add you created a new piece of information. Template is not new, but the piece of information is. And sure, this template might be very simple, too simple, but you can come up with more complex one. And metadata is data. You can create templates in similar manner to how you create new pieces of information using them.
And labs training AI are doing it for years at this point. And it is ever increasing fraction of all training.
If I knew, I'd be rich from deploying it onto a substrate for my own AI.
But that doesn't mean that there isn't something there - the current approach seems at odds with how flesh brains work.
I mean, you can power a human brain with 2x bananas for 4 hours, the energy of which might power an H100 for about 20 seconds. It's obvious that there's something different happening.