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 Because the cheap free models they have access to are extremely out of date, or very limited.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.

We have math PHDs with proofs current LLMs can’t become AGI, because they’ll always have a context issue

I would love it if you’d point me at these mathematical proofs.