The people most qualified to make an educated guess simultaneously have a direct financial incentive to claim that it is in reach within a few years. The only one who doesn't seem to care all that much is Le Cun.

When you see these claims it's important to frame the assertion contextually as in the transformer generation, AGI is 10+ years away. This does not, however, account for the next architecture that will do more with less.

We might start by trying to define what AGI exactly is. It's an elusive goal.

> It's really hard to argue that LLM's don't have intelligence in the way the earthworms do.

It's really easy to argue, actually. LLMs have intelligence the way humans online do. An earthworm is highly specialized for what it does and exists in a completely different context - I doubt an LLM would be successful guiding a robotic earthworm around since all it knows about earthworms is what researchers have observed and documented. The actual second-to-second experience of being an earthworm is not accessible as training data to an LLM.

Edit:

This is true almost by definition. An LLM (Large Language Model) can't have intelligence that's not expressible in language and earthworms are notoriously shy in interviews.

Sunk cost fallacy? What percentage of the public has actually invested the billions/trillions and is now demanding something to show for it? I'm not sure the average joe wants copilot in their outlook, but sure as hell someone wants it in there

because people hedge their bets almost always. basically how likely something is vs costs vs what everybody else is doing vs how you are personally affected.

So in case of the current AI there are several scenarios where you have to react to it. For example as a CEO of a company that would benefit from AI you need to demonstrate you are doing something or you get attacked for not doing enough.

As a CEO of an AI producing company you have almost no idea if the stuff you working on will be the thing that say makes hallucination-free LLMs, allows for cheap long term context integration or even "solve AGI". you have to pretend that you are just about to do the latter tho.

Bots and paid trolls online pushing a narrative.

With a whole manual of rhetorical tactics.

Because "the public" isn't one person or even one cohesive group. Some see the manipulation, and point it out. Others don't see it, or ignore it when it's pointed out.

And why ignore it? Because they don't want to believe it's manipulation, because it promises large numbers of dollars, and they want to believe that those are real.

You can tell by the post history.

It's just like with the fake StackOverflow reputation and fake CodeProject articles in the past.

Same people at it again but super-charged.

ChatGPT has done too many things that "a computer can't do". The "AI effect" denial is strong, but it has its limits.

I've read this multiple times and disagree.

If I had an AGI that designs me a safe, small and cheap fusion reactor, of course I would be interested in that.

My intelligence is intrinsically limited by my biology. The only way to really scale it up is to wire stuff into my brain, and I'd prefer an AGI over that every day.

Well said!

>Yes, and most with a background in linguistics or computer science have been saying the same since the inception of their disciplines

I'm not sure what authority linguists are supposed to have here. They have gotten approximately nowhere in the last 50 years. "Every time I fire a linguist, the performance of the speech recognizer goes up".

>Grammars are sets of rules on symbols and any form of encoding is very restrictive

But these rules can be arbitrarily complex. Hand-coded rules have a pretty severe complexity bounds. But LLMs show these are not in principle limitations. I'm not saying theory has nothing to add, but perhaps we should consider the track record when placing our bets.

Why would language restrict LLMs?

"Language" is an input/output interface. It doesn't define the internals that produce those inputs and outputs. And between those inputs and outputs sits a massive computational process that doesn't operate on symbols or words internally.

And, what "clearer milestones" do you want exactly?

To me, LLMs crushing NLU and CSR was the milestone. It was the "oh fuck" moment, the clear signal that old bets are off and AGI timelines are now compressed.

Can they please do my laundry then?

It's plausible, in 2026, we are going to send to Mars fully autonomous humanoid robots, so AGI is right around the corner.

https://youtu.be/TsNc4nEX3c4?t=5

This has been an argument from the 60s onwards

Majority of people think they are better than average drivers.

Surely those models are not smarter than _you_, right?

If this is true then almost all of the jobs in the world would already be replaced by AI. Sure, the model might be better than most people at lots of things but there are still tasks that human children find easy and AI struggles with. I wouldn't call being better at something than humans being "smarter" than them; if you do, calculators must be smarter than humans since they have been better at adding up numbers than us for a long time.

At analyzing and reproducing language.. words, code etc sure because at their core they are still statistical models of language. But there seems to be growing consensus that intelligence requires modeling more than words.

But they don't have agency and who would trust them unattended anyway (at their current capabilities)?

Not sure why you are being downvoted. Seems like lot of people with high ego are not ready to accept the truth that a human has way less knowledge than a world encyclopedia with infinite and practically perfect memory.