Top economist warns that the AI math doesn’t make sense: 'Profits are currently being funded by investors rather than earned from customers'

Soon™

The bubble gonna poof?

Either that, or the rich and corps will go all in. The point was always to replace human labor, just depends how far from that they think we are. People still see a report an AI did something stupid and laugh at the idea of it replacing us, but just 5 years ago we wouldn’t have believed the things it can do today.

We can’t believe what it does not, or six agos what it does then. The shit is moving faster then literally anyone really seems to understand.

The avg person that makes fun of ai, seems to still think they have the same problems they had 2-3 years. Because the cheap free models they have access to are extremely out of date, or very limited.

The actual real deal big boy models are so far beyond what your avg even extremely technical user understands. Unless you are actively watching following and using the models you just flat out have no clue just how fast this shit is sprinting.

It’s got plenty of problems and the growth is not across every aspect of it equally. So it’s really easy to point and laugh at a particular point it’s struggling with while it skips ahead in other regards.

It’s wild. The progress is just as unsustainable as the profits are bad. As long as that progress keeps sprinting the bad profits flat out don’t matter.

IT WILL hit critical mass to replace your avg idiot long before the profit problem really hits at this rate.

The bigger problem is that even if it replaces people that profit problem doesn’t go away. So it will just hit AFTER people are replaced. And that’s a even worse outcome then replacing people.

We NEED the bubble to pop before that point and the industry recalibrates to a sustainable model.

Else we will have mass job loss promptly followed by a massive bubble popping and economy collapse AND companies flopping and job opportunity losses as places closing shop so there won’t even be jobs to back to.

It could get REALLY fucking bad.

Disagree.

It is true there were massive strides in the last 8 years. But fundamentally, the tech is still the same large language model it was before, just bigger and better optimized.

It’s like going from an ancient, slow, Ford Model T that topped out at 45mph to a Bugatti that can do 260mph in 8 short years. It’s impressive, it boosts productivity, it is a marvel of modern technology, but that’s not my point of contention.

The issue is that AI companies have been funded on the promise that with enough advancements and upgrades this tech will achieve AGI. Which is an absurd statement to anyone in the field actually developing these things. That is the equivalent of promising that this 260mph Bugatti, with a few years of upgrades and advancements, will become a Harrier Jump Jet!

It’s just not happening, a fundamental shift in model architecture or technology used is needed. And from what we’ve seen so far, no one has discovered any.

The issue is that AI companies have been funded on the promise that with enough advancements and upgrades this tech will achieve AGI. Which is an absurd statement to anyone in the field actually developing these things. That is the equivalent of promising that this 260mph Bugatti, with a few years of upgrades and advancements, will become a Harrier Jump Jet!

A better analogy is promising that a toddler will, with enough knowledge and training, eventually become a heart surgeon.

15 years ago the assumption with AGI was that we needed some paradigm shift in technology to create it, but after transformer technology was invented (the T in GPT), and it was trained on a lot of information, we discovered an emergent property that it could take natural language queries and answer them with its knowledge base-- which was unexpected and unintended.

While science can always end up going down the wrong path, the current mainstream stance is that we were wrong about needing new technology for AGI; it seems that AGI may be a function of information and training, on hardware we already have. Hence all the data centers being built.

Anyone who says with certainty that it will result in AGI is just as wrong as someone who says with certainty that it won’t.

That analogy makes the assumption that LLMs are dormant baby AGIs. There is no evidence that AGI is just a bigger and better curated LLM.

That is where the evidence points. Now, I don’t want to oversell it: “where the evidence points” is wildly different than “exactly how it works”.

We have an emergent property that we don’t understand, but we can reliably increase the functionally and complexity of that emergent property as a function of training data and available compute. Does that mean that there isn’t some threshold where that stops working? No, there certainly could be a point where throwing more information and compute has no effect. We just don’t know. However, so far, there is no evidence such a barrier exists, and everyone is racing to find out.

I think that is where the hopes and hype point. The evidence, that which is gathered through controlled studies, points to an upper limit to this technology that does have emergent properties, but not ones that amount to cognition. That evidence also points to other hurdles, such as cognitive damage to the user and context windows nowhere near that of even a simpleminded creature, let alone a sapient one like a human.

The core problem is that these models are fixed; they are the same on day 1000 as they were on day 1. All their “learning”, as it were, happens in training before it is released. Everything it appears to learn after that date is contained in the rolling context window. Since they already have literally all the RAM they can get their hands on and are still at least an order of magnitude away from where they need to be on that, this technology either can’t do it or, at best, is so inefficient an approach that it can’t be done with all the planet’s resources.

Sometimes, especially in abstract constructions like software, you can start down the wrong path early and have to start over, because there is no path from where you are to where you need to get. In this case, they may have done that to the extreme, blinded by the lucrative prospects.

As far as I am aware, AGI does not imply sapience, consciousness, or whatever. You seem to believe it does. A high level Google search seems to suggest that I’m correct. Is there some reason you are lumping sapience with AGI?

I’m not sure if the rest of your comment presupposes this, so I’ll wait to comment on where I think you’re mistaken.

I dont believe it requires sapience; that is what the marketers are saying. The AI boom (and many historic boom cycles) is predicated on marketing and sentiment, not facts and data. That is why they always pop; the facts dont back up the hype.

The fact that your search results turn up results that align with the marketing is just the marketing working.

Look–neither of us are data scientists, but we do have eyes. If this is working, where’s the company with runaway success creating unimagined leaps in productivity and technology? We’re pouring a whole planet’s with of resources in and nothing much is coming out. If we spent this much on world hunger, everyone would be obese by now.

I dont believe it requires sapience; that is what the marketers are saying. The AI boom (and many historic boom cycles) is predicated on marketing and sentiment, not facts and data. That is why they always pop; the facts dont back up the hype.

I think there is some confusion. I do not believe AGI implies sapience, nor does Google, and now it seems that you don’t either. So who is discussing sapience?

If this is working, where’s the company with runaway success creating unimagined leaps in productivity and technology?

Hypothetically speaking, what do you think this would look like?

The marketers are not using the word “sapience”, as that word would require defining for the layman. They are claiming AI will usher in an era of human prosperity by taking over our work and big decisions to do them more efficiently–tasks that sound to almost everyone to require advanced decision-making and thought, the hallmarks of sapience and cognition. This is largely besides the point, though.

I think that if this were successful, you would see at least some early adopting companies coming up aces. Some company would have double the productivity with half the workforce, and use that to absolutely devour their market segment by undercutting everyone else on price because their operating costs are so much lower than the competition. I’d see a software company adopt breakneck software release cycles with substantial, material stability and performance improvements with each. I’d see some company anywhere suddenly begin to outperform their former selves and be able to convincingly point to AI as where their improvements came from. The only one like that I can think of is NVidia, who are rich strictly because they’re selling shovels in the gold rush.

I think that if this were successful…

What it would look like is layoffs from a company without a change in output/productivity. Notably, we’re not at AGI yet, so I wouldn’t expect sci-fi levels of change.

That is one thing it could look like which is captured in my examples. We dont see any company like that. Remember that stock valuation is not, in the present day, correlated to any business metric. There are companies with huge valuations that have never netted $1 (like these AI companies, for example). So, even in your narrower example, there are no companies I have heard of that meet its criteria.

There would necessarily be a lag time between layoffs and unchanged productivity. And even then, if we’re being fair, that’s not conclusive evidence of AI being useful; it could just be that they had more employees than they needed.

My point is more that I’m not sure we’d see an obvious sign that AI was changing the market yet.

Elon Musk, the apparent thought leader of the tech sector and mover of markets, claims we will be in a post-scarcity AI-fuelled utopia by 2036. Since his words move the market, clearly the market heeds his words.

In that context, it seems quite modest to expect obvious material gains from using AI by now. When the car was invented, you could prove its utility immediately by getting between to places faster than ever before. When space flight was invented, you could prove its utility by relaying messages around the planet. When insulin were invented, you could prove its utility by curing people bed-ridden awaiting death.

My point is, real paradigm-shifting inventions demonstrate how they’ll do that right away, in an undeniable way. So, AI is either not a paradigm shifting technology, or its not done yet and people are buying a half-baked product.

Elon Musk is an idiot, and you’ve already noted that the market doesn’t track reality.

The paradigm shifting invention was the transformer (the T in GPT). If you’ll forgive a shitty analogy, it’s like someone invented a microscope and you’re asking why we don’t yet have insulin. Not having insulin doesn’t make the microscope useless.

As far as these things go, AI is improving at a breakneck speed-- hence why so many people in the field are begging for a pause in development. We don’t really understand why this technology works as well as if does, and that has a lot of people worried that we’re going to do something dangerous without understanding what we did.

Your example is another one that illustrates my point. When they invented the microscope, they could instantly demonstrate its utility in it’s ability to observe previously invisibly tiny things. The following inventions that enabled are great, but the microscope itself was great, too, and all could see why.

AI is almost all hype. When anyone asks what it can do that was impossible or too difficult before, people point to what they think it will do, yourself included.

So, again, what previously intractable problem does AI solve? Please do not include answers of problems you think it might one day solve. Like the microscope can immediately let you see tiny things, what does the AI let you do that was impossible before? Bonus points if what it does is worth spending a planet’s worth of resources on.

When they invented the microscope, hey could instantly demonstrate its utility in it’s ability to observe previously invisibly tiny things.

I assure you that 400 some odd years ago, most people would not have grasped the utility in the microscope. Just like many people today don’t understand what the transformer has done for machine learning.

But some could, and they could articulate their reasoning. “Machine learning” is not even necessarily a path to anything. Its hard to argue that against your example, which is literally unlocking secrets of the universe.

Again, you’re using 400+ years of hindsight to inform your conclusion. “Looking at small things” doesn’t immediately imply “unlocking the secrets of the universe”, it’s only after hundreds of years of building on that invention that you can easily point to that conclusion.

And admittedly the analogy was not great, I’m just trying to get across that you’re looking at the output of the invention and asking “is that it”? But we’ve only had this technology for a decade or so, and it’s only really been public facing for, what, 4 years?

These various technologies we refer to as “AI” are not yet at the point where they can replace any human at any task, but they can replace some humans at some tasks, and as far as the evidence shows, we can continue to improve it with more training and more compute. They are writing prose well enough to pass as humans, solving math problems we haven’t been able to solve for decades, writing medium complexity code in minutes instead of days-- the technology isn’t solving all the world’s problems and ushering in a post-scarcity utopia, but no one is claiming it is, today. Will it? I doubt it, but that’s more to do with capitalism corrupting everything it touches than anything else.

If you think “AI” is not useful, you’re probably considering a very narrowly defined type of “AI” in a very narrowly defined scenario where AI does not perform well.

Edit: I want to take a second to say that I’ve enjoyed this conversation with you. I can’t say that about many conversations on this topic. This isn’t me ending the conversation.

I’m not even drawing a conclusion anymore. I’m asking for anyone anywhere to point to the previously impossible thing that AI lets me do. Even if that thing is of questionable utility, what is it? I just want an answer to that question.

Then, we can start talking about if that’s worth the cost. Most previous inventions cost someone’s life savings, or corporate focus on technology. This one’s costing us the GDP of South Korea, so it better be good. Like “the microscope” or “the wheel” good.

previously impossible thing that AI lets me do

When did anyone ever claim that? It’s not going to break the laws of physics.

If you do it on a computer, current AI (an umbrella term) can probably make it easier for you to do, if not just do it for you.

Everyone’s claiming that! Every invention allows someone to do something that was previously impossible. Humans couldn’t travel faster than a horse can run until the car was invented. Humans couldn’t see microbes before the microscope was invented. People couldn’t drag more than 10x their body weight until the wheel was invented. People couldn’t catch a marlin until the net was invented.

I am trying to resist the notion that youre being willfully obtuse if you aren’t equating invention with increasing what is possible.

I didn’t realize you meant that. In my mind humans could drag stuff and catch fish but the inventions made it easier or more efficient.

In that view, pretty much anything on a computer can be done easier or more efficient with AI. Same as a net or a wheel. Just Google anything it is you might want to do on a computer and add “using AI” and you’re likely to find a tool to do it. If you have the computer for it, you can download an open weight model to do locally (though probably not as well as using the crazy compute associated with using an API model.

Also, as agentic AI improves, we’ll see the scarcity of attention decrease and maybe vanish entirely. It’s not always obvious, but much of how our society is structured assuming that people have limited agency.

Do you mind sharing what your profession is?