I don't think AGI is right around the corner

LLM are a compressed version of their training dataset with a text based interactive search function.

LLMs require the sum total of human knowledge to ape what you can find on google, meanwhile Ramanujan achieved brilliant discoveries in mathematics using nothing but a grade school education and a few math books.

Yes, but you're missing their ability to interpolate across that dataset at retrieval time, which is what makes them extremely useful. Also, people are willing to invest a lot of money to keep building those datasets, until nearly everything of economic value is in there.

not everything of economic value is data retrieval

LLMs are useful in that respect. As are media diffusion models. They've compressed the physics of light, the rules of composition, the structure of prose, the knowledge of the internet, etc. and made it infinitely remixable and accessible to laypersons.

AGI, on the other hand, should really stand for Aspirationally Grifting Investors.

Superintelligence is not around the corner. OpenAI knows this and is trying to become a hyperscaler / Mag7 company with the foothold they've established and the capital that they've raised. Despite that, they need a tremendous amount of additional capital to will themselves into becoming the next new Google. The best way to do that is to sell the idea of superintelligence.

AGI is a grift. We don't even have a definition for it.

You phrase it as a diss but "Yeah LLM suck, they aren't even as smart as Ramanujan" sounds like a high praise to me.

Most economic value is not data retrieval

The stock market is the root for the majority of all the world's economic value, and has almost-exclusively been data retrieval since 2001.

I an not an expert but I have a serious counterpoint.

While training LLMs to replicate the human output, the intelligence and understanding EMERGES in the internal layers.

It seems trivial to do unsupervised training on scientific data, for instance, such as star movements, and discover closed-form analytic models for their movements. Deriving Kepler’s laws and Newton’s equations should be fast and trivial, and by that afternoon you’d have much more profound models with 500+ variables which humans would struggle to understand but can explain the data.

AGI is what, Artificial General Intelligence? What exactly do we mean by general? Mark Twain said “we are all idiots, just on different subjects”. These LLMs are already better than 90% of humans at understanding any subject, in the sense of answering questions about that subject and carrying on meaningful and reasonable discussion. Yes occasionally they stumble or make a mistake, but overall it is very impressive.

And remember — if we care about practical outcomes - as soon as ONE model can do something, ALL COPIES OF IT CAN. So you can reliably get unlimited agents that are better than 90% of humans at understanding every subject. That is a very powerful baseline for replacing most jobs, isn’t it?

Unfortunately LLMs fail even basic logic tests given to children so definitely not high praise. I'm just highlighting the absurd amount of data they need versus humans to highlight that they're just spitting out regressions on the training data. We're talking data that would take a human countless thousands of lifetimes to ingest. Yet a human can accomplish infinitely more with a basic grade school education.

Come on. The stock market is not just data retrieval. The statement doesn’t even make sense.

It makes perfect sense, and I meant what I said.

60% of all US equity volume is pure high-frequency trading, and ETFs add roughly another 20% that’s literally just bots responding to market activity and bearish-bullish sentiment analysis on public(?) press releases. 2/3 of trading funds also rely on external data to price in decisions, and I think it was around 90% in 2021 use trading algorithms as their determining factor for their high-frequency trade strategies.

At its core, the movements that make up the market really IS data retrieval.

Sure, the market, but HFT is relatively tiny as a market and the profit it brings. Not to mention, it's essentially a zero-sum game.

Brought to you by your favorite Google LLM search result:

"The global high-frequency trading (HFT) market was valued at USD 10.36 billion in 2024 and is projected to reach USD 16.03 billion by 2030"

(unverified by a human, use at your own risk).

>"The global high-frequency trading (HFT) market was valued at USD 10.36 billion in 2024 and is projected to reach USD 16.03 billion by 2030"

>

> (unverified by a human, use at your own risk).

Honorable for mentioning the lack of verification; doing so would have dissolved the AI's statement, but jury's out on how much EXACTLY:

Per https://www.sciencedirect.com/science/article/abs/pii/S03784...:

"While estimates vary due to the difficulty in ascertaining whether each trade is an HFT, recent estimates suggest HFT accounts for 50–70% of equity trades and around 50% of the futures market in the U.S., 40% in Canada, and 35% in London (Zhang, 2010, Grant, 2011, O’Reilly, 2012, Easley et al., 2012, Scholtus et al., 2014)"

In my original reply, I used the literal median of that spectrum @ 60%

Jane Street - who has recently found themselves in hot water from the India ban - disputes that AI summary ALONE. Per https://www.globaltrading.net/jane-street-took-10-of-of-us-e... , Jane Street booked 20.5B in trading revenue, primarily though HFT's, just in 2024.

Brought to you by someone who takes these market movements too seriously for their own good.

The stock market does not grow potatoes.

And potatoes don't grow nearly as much economic value within industrial societies - as they do in, say, agrarian ones. All to say, I don't understand your point.

The stock market does not make movies either.

Humans can achieve more within one (or two, or a few) narrowly scoped field(s), after a lot of hard work and effort. LLMs can display a basic level of competency (with some mistakes) in almost any topic known to mankind. No one reasonably expects a LLM to be able to do the former, and humans certainly cannot do the latter.

You're comparing apples and oranges.

Also, your comparison is unfair. You've chosen an exceptional high achiever as your example of a human to compare against LLMs. If you instead compare the average human, LLMs don't look so bad even when the human has the advantage of specialisation (e.g. medical diagnostics). A LLM can do reasonably well against an average (not exceptional) person with just a basic grade school education if asked to produce an essay on some topic.

>Humans can achieve more within one (or two, or a few) narrowly scoped field(s), after a lot of hard work and effort.

>No one reasonably expects a LLM to be able to do the former

I can feel Sam Altman's rage building ...

Anthropomorphization is doing a lot of heavy lifting in your comment.

> While training LLMs to replicate the human output, the intelligence and understanding EMERGES in the internal layers.

Is it intelligence and understanding that emerges, or is applying clever statistics on the sum of human knowledge capable of surfacing patterns in the data that humans have never considered?

If this were truly intelligence we would see groundbreaking advancements in all industries even at this early stage. We've seen a few, which is expected when the approach is to brute force these systems into finding actually valuable patterns in the data. The rest of the time they generate unusable garbage that passes for insightful because most humans are not domain experts, and verifying correctness is often labor intensive.

> These LLMs are already better than 90% of humans at understanding any subject, in the sense of answering questions about that subject and carrying on meaningful and reasonable discussion.

Again, exceptional pattern matching does not imply understanding. Just because these tools are able to generate patterns that mimic human-made patterns, doesn't mean they understand anything about what they're generating. In fact, they'll be able to tell you this if you ask them.

> Yes occasionally they stumble or make a mistake, but overall it is very impressive.

This can still be very impressive, no doubt, and can have profound impact on many industries and our society. But it's important to be realistic about what the technology is and does, and not repeat what some tech bros whose income depends on this narrative tell us it is and does.

Revenue is not profit

The percentage is irrelevant without knowing how they really work and how much profit they make. They could be at 95% with 0.1% of margin it wouldn’t mean much for the market.

At the end of the day talking about HFT this way is to not know what they do and what service they offer to the market. Overall they are not trending makers but trend followers.

Exactly I am so tired to hear about AI… And they are not even AI! I am also losing faith in this field when I see how much they all push so much hype and lies like this instead of being transparent. They are not AGIs not even AIs… For now they are only models and your definition is a good one

Because hypetrain.

Yeah, I think many investors do expect that ...

Indeed 90% problems can be solved by googling and that's what LLMs do. AGI is expected to be something more than a talking encyclopedia.

I hate the "accessible to the layperson" argument.

People who couldn't do art before, still can't do art. Asking someone, or something else, to make a picture for you does not mean you created it.

And art was already accessible to anyone. If you couldn't draw something (because you never invested the time to learn the skill), then you could still pay someone else to paint it for you. We didn't call "commissioning a painting" as "being an artist", so what's different about "commissioning a painting from a robot?"

  > 60% of all US equity volume

Volume is not value.

The stock market is not the root of the value, it's where the value (and plans for generating more) is put to a popularity contest.

20 billion is a tiny fraction of the value represented in the stock exchange (and a tiny fraction of the profits made on it). HFT by its nature makes for a lot of volume but that's just a lot of shuffling of things around to peel a tiny fraction of value off the top, it's far from driving the market and the market isn't what makes the value in the first place.

> I hate the "accessible to the layperson" argument.

Accessible to a layperson also means lowering the gradient slope of learning.

Millions of people who would have never rented a camera from a rental house are now trying to work with these tools.

Those publishing "slop" on TikTok are learning the Hero's Journey and narrative structure. They're getting schooled on the 180-degree rule. They're figuring out how to tell stories.

> People who couldn't do art before, still can't do art. Asking someone, or something else, to make a picture for you does not mean you created it.

Speak for yourself.

I'm not an illustrator, but I'm a filmmaker in the photons-on-glass sense. Now I can use image and video models to make animation.

I agree that your average Joe isn't going to be able to make a Scorsese-inspired flick, but I know what I'm doing. And for me, these tools open an entire new universe.

Something like this still takes an entire week of work, even when using AI:

https://www.youtube.com/watch?v=tAAiiKteM-U

There's lots of editing, rotoscoping, compositing, grading, etc. and the AI models themselves are INSANELY finicky and take a lot of work to finesse.

But it would take months of work if you were posing the miniatures yourself.

With all the thought and intention and work that goes into something like this, would you still say it "does not mean you created it"? Do you still think this hasn't democratized access to a new form of expression for non-animators?

AI is a creative set of tools that make creation easier, faster, more approachable, and more affordable. They're accessible enough that every kid hustling on YouTube and TikTok can now supercharge their work. And they're going to have to use these tools to even stay treading water amongst their peers, because if they don't use them, their competition (for time and attention) will.

> Superintelligence is not around the corner. OpenAI knows this and is trying to become a hyperscaler / Mag7 company with the foothold they've established and the capital that they've raised.

+1 to this. I've often wondered why OpenAI is exploring so many different product ideas if they think AGI/ASI is less than a handful of years away. If you truly believe that, you would put all your resources behind that to increase the probability / pull-in the timelines even more. However, if you internally realized that AGI/ASI is much farther away, but that there is a technology overhang with lots of products possible on existing LLM tech, then you would build up a large applications effort with ambitions to join the Mag7.

With Google I can demonstrate a wide breadth of knowledge too. LLM's aren't unique in that aspect.

e.g. farming

yeah I've been thinking about them as stochastic content addressable memory. You can put as many next = userInput; while(true's) { next = mem[next]; } around them as you need in different forms. Single shot. Agents. etc and get wildly cool results out, but it's gated by some of the limitations there.