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.

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

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.

I'm convinced it'll be in the form of emergence and it won't immediately be known when it's started.

It may very well already be here, but the feedback loops are excruciatingly long and expensive.

It's not quite the same category as magic spells. Kurzweil's prediction has been for 2029 for the last thirty years or so based on Moore's law type stuff. The logic I think is roughly project the hardware improvements, which has worked well, and then add on about five years to sort the software. Time will tell on the second one.

that post didn't even define AGI, right?

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 "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.

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.

This comment can be easily read in Slavoj Žižek’s voice

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.

Whether or not that question is interesting is hardly relevant in this particular discussion. Companies building this technology are marketing it as if computers can think. They're telling us they can, and people are buying into it based on that claim.

So that quote doesn't reconcile the extraordinary claims of one side with the skepticism of the other.

And also, no disrespect to Dijkstra, but that sentiment is a bit shortsighted. If we could make computers think, it would have a profound impact on humanity. This is why there is so much excitement around this. We've been imagining this scenario for centuries, and we hope that this time around we can finally crack it. So comparing that achievement with something we can produce with classical technology is... uninspiring? Underwhelming? Selling ourselves short? I can't quite put it into words, but the possibility of answering that question would certainly be very interesting.

Well said!

LLMs do NOT have intelligence. Achieving AGI would mean solving self-driving cars, replacing programmers, scientist, etc. All things LLMs are currently unable to do in a way that replaces humans.

There's a huge gap between what Gemini 3 can do and what AGI promises to do. It's not just a minor "technical definition".

The winner if there is one will be clear. Making a machine that's as good or better than human at most tasks is the turning point but doesn't demonstrate the win. Applying it for self-improvement making superintelligence which is when the winner will be racing with rockets vs bicycles. I don't know how this will play out--will the second one to achieve it always be behind? It probably depends on the difference in timing and other factors.

The winner will be the one that announces "we have AGI" based on their own definition, and the rest of the world actually agrees with them.

The upside of being right is massive, but the downside of prematurely announcing AGI only for the rest of the world to disagree with your definition is probably tremendously large.

It's a bit of a catch-22

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.

It has the logical inconsistency of good LLM slop like:

"AGI is not possible"

combined with

"Does this mean AI progress will stall? Absolutely not."

Yup, clocked it in seconds. There's something especially perverse about reading AI slop waxing poetic about AI slop.

Outside of internet debates I don't believe it matters. Much like the discussion of when machines will be treated like people, that's already happening without applying a definition.

>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.

With all due respect to Arthur C. Clarke, I think science education is the only thing standing between us and even bigger scams and absolute chaos in the streets.

What is understood by a scientist isn't so far ahead from what the layperson understands these days compared to when Clarke wrote that.

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

“ Machines will be capable, within twenty years, of doing any work that a man can do.” - Herbert Simon, 1965

Could you please make your substantive points without breaking the site guidelines? They include:

"When disagreeing, please reply to the argument instead of calling names. 'That is idiotic; 1 + 1 is 2, not 3' can be shortened to '1 + 1 is 2, not 3."

https://news.ycombinator.com/newsguidelines.html

> 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.

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.

Can they please do my laundry then?