Technology

I've ran some college hw through 4o just to see and it's remarkably good at generating proofs for math and algorithms. Sometimes it's not quite right but usually on the right track to get started.

In some of the busier classes I'm almost certain students do this because my hw grades would be lower than the mean and my exam grades would be well above the mean.

The answer is that it's all about "growth". The fetishization of shareholders has reached its logical conclusion, and now the only value companies have is in growth. Not profit, not stability, not a reliable customer base or a product people will want. The only thing that matters is if you can make your share price increase faster than the interest on a bond (which is pretty high right now).

To make share price go up like that, you have to do one of two things; show that you're bringing in new customers, or show that you can make your existing customers pay more.

For the big tech companies, there are no new customers left. The whole planet is online. Everyone who wants to use their services is using their services. So they have to find new things to sell instead.

And that's what "AI" looked like it was going to be. LLMs burst onto the scene promising to replace entire industries, entire workforces. Huge new opportunities for growth. Lacking anything else, big tech went in HARD on this, throwing untold billions at partnerships, acquisitions, and infrastructure.

And now they have to show investors that it was worth it. Which means they have to produce metrics that show people are paying for, or might pay for, AI flavoured products. That's why they're shoving it into everything they can. If they put AI in notepad then they can claim that every time you open notepad you're "engaging" with one of their AI products. If they put Recall on your PC, every Windows user becomes an AI user. Google can now claim that every search is an AI interaction because of the bad summary that no one reads. The point is to show "engagement", "interest", which they can then use to promise that down the line huge piles of money will fall out of this pinata.

The hype is all artificial. They need to hype these products so that people will pay attention to them, because they need to keep pretending that their massive investments got them in on the ground floor of a trillion dollar industry, and weren't just them setting huge piles of money on fire.

The article does mention that when the AI bubble is going down, the big players will use the defunct AI infrastructure and add it to their cloud business to get more of the market that way and, in the end, make the line go up.

Models are not improving, companies are still largely (massively) unprofitable, the tech has a very high environmental impact (and demand) and not a solid business case has been found so far (despite very large investments) after 2 years.

That AI isn't going anywhere is possible, but LLM-based tools might also simply follow crypto, VR, metaverses and the other tech "revolutions" that were just hyped and that ended nowhere. I can't say it will go one way or another, but I disagree with you about "adjustment period". I think generative AI is cool and fun, but it's a toy. If companies don't make money with it, they will eventually stop investing into it.

Also

Today’s hype will have lasting effects that constrain tomorrow’s possibilities

Is absolutely true. Wasting capital (human and economic) on something means that it won't be used for something else instead. This is especially true now that it's so hard to get investments for any other business. If all the money right now goes into AI, and IF this turns out to be just hype, we just collectively lost 2, 4, 10 years of research and investments on other areas (for example, environment protection). I am really curious about what makes you think that that sentence is false and stupid.

It's fucking fantastic news, tbh.

Here's my take, let them dismiss it.

Let em! Remember Bitcoin at $15k after 2019?

Let em! And it's justified! If Ai isn't important right now, then why should its price be inflated to oblivion? Let it fall. Good! Lower prices for those of us that do see the value down the road.

That's how speculative investment works. In no way is this bad. Are sales bad? Sit back and enjoy the show.

Where, in that position piece, do they mention o3? Who "proved" this?

Additionally, I'm pretty sure that this "ARC AGI" benchmark is not using the same definition of AGI that you linked to by DeepMind. Conflating them is misleading. There is already so much misinformation out there about "AI", don't add to it.

Lastly, I struggle to take at face value essays written by for-profit companies claiming they have AGI (that DeepMind paper links to OpenAI essays). They only stand to gain monetarily by claiming that their AI is an AGI (to be clear, this is an opinion; I do not have evidence to suggest that OpenAI is being disingenuous).

It's a bubble because OpenAI spend $2.35 for every $1.00 they make. Yes, you're mathing right, that is a net loss.

It's a bubble because all of the big players in AI development agree that future models will cost exponentially more money to train, for incremental gains. That means there is no path forward that doesn't intensely amplify the unprofitability of an already deeply unprofitable industry.

It's a bubble because newer models with better capabilities only cost more and more to run.

It's a bubble because as far as anyone knows there will never be a solution to the hallucination problem.

It's a bubble because despite investments treating it as a trillion dollar industry, no one has yet figured out a trillion dollar problem that AI can solve.

You're trying on a new top of the line VR headset and saying "Wow, this is incredible, how can anyone say this is a bubble?" Its not about how cool the tech is in isolation, it's about its potential to effect widespread change. Facebook went in hard on VR, imagining a future where everyone worked from home while wearing VR headsets. But what they got was an expensive toy that only had niche uses.

AI performs do well on certain coding tasks because a lot of the individual problems that make up a particular piece of software have already been solved. It's standard practice to design programs as individual units, each of which performs the smallest task possible, and which can then be assembled to complete more complex tasks. This fits very well into the LLM model of assembling pieces into their most likely expected configurations. But it cannot create truly novel code, except by a kind of trial and error mutation process. It cannot problem solve. It cannot identify a users needs and come up with ideal solutions to them. It cannot innovate.

This means that, at best, genAI in the software world becomes a tool for producing individual code elements, guided and shepherded by experienced programmers. It does not replace the software industry, merely augments it, and it does so at a cost that many companies simply may not feel is worth paying.

And that's its best case scenario. In every other industry AI has been a spectacular failure. But it's being invested in as if it will be a technological reckoning for every form of intellectual labour on earth. That is the absolute definition of a bubble.

o3 made the high score on ARC through brute force, not by being good. To raise the score from 75% to 87% required 175 times more computing power, but exactly stunning returns.

Unless we invent cold fusion between the next 5 years, they will never be economical. They are the most energy inefficient thing ever invented by humanity and all prediction models state that it will cost more energy, not less, to keep making them better. They will never be energy efficient nor economical in their current state, and most companies are out of ideas on how to shake it up. Even the people who created generative models agree that they have just been brute forcing by making the models larger with more energy consumption. When you try to make them smaller or more energy efficient, they fall off the performance cliff and only produce garbage. I'm sure there are researchers doing cool stuff, but it is neither economical nor efficient.

Your example is strange because, as far as I know, GPTs aren't economical either.

Why is it getting an AGI stamp now? I was under the impression humanity has not delivered a sentient AI? Which is what the AGI title was supposed to be used for...has that been pulled back again?