$800B, to be clear is the claim, not $80B.

Clearly I need to read slower. Thanks. :)

While AGI might be the Holy Grail, AI doesn’t need to be general human-level to be useful and profitable.

it just needs us to wait one more year right?

It's already quite useful. While not all AI service providers are profitable, I've worked on projects that saved a lot of money for the company - a lot more than it cost us running the servers.

>> There is even a recent paper that points out that LLMs will never become AGI.

can you share a link?

Took me a while to find again, as there are a lot of such papers in this area.

https://www.arxiv.org/pdf/2511.18517

Welcome to the world of papers. Have a read and get back to us. Dismissing out of hand is rarely constructive.

took me a while but i read it. thought it was actually a pretty good and well researched paper that does a good job rationalizing its thesis. thanks for sharing

Ad hominem right out of the gate? Really?

Is this AI paper written by a reputable subject matter expert? It seems to be written by a physicist and also be the only academic work by this author in English

So you are dismissing it because of that? Certainly read the paper first and attack the arguments, not the author. It even has 10 pages of citations.

I have read it. It is nothing new on the subject, but it was just the recent paper I saw on HN and the person was asking for the link.

The crux is an LLM is and can never be intelligent in the sense of an AGI. It is easier to think of it as a way to store and retrieve knowledge.

How many articles on this topic do we imagine there are? Thousands? Hundreds of thousands? It is hopeless to read every one by any author, no matter how unrelated to the domain, and judge them individually on their merits. Being a subject domain expert is not a perfect measure of paper quality but it's the only feasible way to make a first pass at filtering.

Even if I did read it, I have no hope of understanding if it has made a fundamental mistake because I don't have the subject matter expertise either.

(I imagine it has made a fundamental mistake anyway: for LLMs to be useful progress toward AGI they don't have to be a feasible way to create AGI by themselves. Innovation very often involves stepping through technologies that end up only being a component of the final solution, or inspiration for the final solution. This was always going to be an issue with trying to prove a negative.)

> It is hopeless to read every one by any author,

It was a paper posted on HN a few days ago and someone asked for the evidence of my statement. I supplied it.

Now if they actually read it and disagreed with what it was saying, I'd be more than happy to continue the conversation.

Dismissing it just because you don't understand is a terrible thing to do to yourself. It's basically sabotaging your intelligence.

Sometimes papers are garbage, but you can only make that statement after you have read/understood it.

Use an LLM if you want.

I was really just asking, not trying to be dismissive. Expertise is an important context to evaluate a piece of writing.

Absolutely. If it is not written by someone who has real world experience and deep knowledge it has no more value than a HN comment.

It's a good read and good citations.

The core piece as quoted from the abstract: "AGI predictions fail not from insufficient compute, but from fundamental misunderstanding of what intelligence demands structurally."

Then goes in detail as to what that is and why LLMs don't fit that. There are plenty other similar papers out there.

It was more of a general principle than about specific paper that I mentioned that :)

Sry to say but the fact that you argue with LLMs never become AGI, you are not up-to-date.

People don't assume LLM will be AGI, people assume that World Models will lead us to AGI.

I personally never asumed LLM will become AGI, i always assumed that LLM broke the dam for investment and research into massivce scale compute ML learning and LLMs are very very good in showing were the future goes because they are already so crazy good that people can now imagine a future were AGI exists.

And that was very clear already when / as soon as GPT-3 came out.

The next big thing will probably be either a LOT more RL or self propelling ai architecture discovery. Both need massive compute to work well but then will potentially provide even faster progress as soon as humans are out of the loop.

> People don't assume LLM will be AGI,

I wish that was true.

> people assume that World Models will lead us to AGI.

Who are these people? There is no consensus around this that I have seen. You have anything to review regarding this?

> as soon as GPT-3 came out.

I don't think that was true at all. It was impressive when it came out, but people in the field clearly saw the limitations and what it is.

RL isn't magical either. Google AlphaGo as an example often required human intervention to get the RL to work correctly.

AlphaGo Zero doesn't need much human intervention at all.

Regarding world models: All the big ones. LeCun, Demis Hassabis, Fei-Fei Li too. And they are all working on it.

LLMs will definitly play some type of role in AGI. After all you can ask an LLM already a lot of basic things like 'what are common tasks to make a tea'. A type of guide, long term fact memory or whatever this can be called.

> AlphaGo Zero doesn't need much human intervention at all

You should research it and not just read news articles. RL did not work and required human intervention numerous times before it got close to what it is now.

Are OpenAI or Anthropic et al seriously building towards “world models”? I haven’t seen any real evidence of that. It seems more like they are all in on milking LLMs for all they are worth.

I mentioned it in my other comment but people like LeCun, Demis Hassabis, Fei-Fei Li do.

There are indications that Open AI is doing this but nothing official as far as i know and i have not heard anything from Anthropic.