What a day to be alive, when people arguing if AGI will be possible in the next 10 years or 20 years.
This has been an argument from the 60s onwards
AGI is not possible even in 10 years
41–50 of 106 posts
Re: AGI is not possible even in 10 years
#42It seems to me by most classical definitions we've basically already reached AGI.
If I were to show Gemini 3 Pro to anyone in tech 10 years ago they would probably say Gemini 3 is an AGI, even if they acknowledged there was some limitations there.
The definition has moved so much that I'm not convinced that even if we see further breakthroughs over the next 10 years people will say we've finally reached AGI because even at that point it's probable there might still be 0.5% of tasks it struggles to compete with humans on. And we're going to have similar endless debates about ASI and the consciousness of AI.
I think all that matters really is utility of AI systems broadly within society. While a self-driving car may not be an AGI, it will displace jobs and fundamentally change society.
The achievement of some technical definition of AGI on the other hand is probably not all that relevant. Even if goal posts stop moving from today and advancements are made such that we finally get 51% of experts agreeing that AGI has been reached there could still be 49% of expert who argue that it hasn't. On the other hand, one will be confused about whether their job has been replaced by an AI system.
I'm sorry - I know this is a bit of a meta comment. I do broadly agree with the article. I just struggle to see why anyone cares unless hitting that 51/49% threshold in opinion on AGI correlates to something tangible.
Re: AGI is not possible even in 10 years
#43> The architecture might just be wrong for AGI. LeCun’s been saying this for years: LLMs trained on text prediction are fundamentally limited. They’re mimicking human output without human experience. Yes, and most with a background in linguistics or computer science have been saying the same since the inception of their disciplines. Grammars are sets of rules on symbols and any form of encoding is very restrictive. W…
>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 restr…
I'm very confused by your comment, but appreciate that you have precisely made my point. There are no "bets" with regard to these topics. How do you think a computer works? Do you seriously believe LLMs somehow escape the limitations of the machines they run on?
Re: AGI is not possible even in 10 years
#44Re: AGI is not possible even in 10 years
#45AGI has already happened. Grok4 and Gemini 3 Pro top models are around the 125-130IQ range. They are rapidly moving towards ASI.
Can they please do my laundry then?
Doing your laundry is a sign of general intelligence? If someone is a quadriplegic and cant do their own laundry, does that mean they arent intelligent?
Re: AGI is not possible even in 10 years
#46According to Clarke's First Law, "When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong."
Re: AGI is not possible even in 10 years
#47> The architecture might just be wrong for AGI. LeCun’s been saying this for years: LLMs trained on text prediction are fundamentally limited. They’re mimicking human output without human experience. Yes, and most with a background in linguistics or computer science have been saying the same since the inception of their disciplines. Grammars are sets of rules on symbols and any form of encoding is very restrictive. W…
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.
Re: AGI is not possible even in 10 years
#48It feels like any time scale on AGI is basically just made up. Since no one has any idea of how to get there, how could you possibly estimate how long it will take? We could stumble on some secret technique that unlocks AGI tomorrow or it could be literally impossible. You might as well ask how long until humans can cast magic spells.
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.
Re: AGI is not possible even in 10 years
#49Earlier quoted context omitted.
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.
This is inconsistent with people like Hassabis or Sutskever giving time frames while also saying that LLMs won't get us to AGI.
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Re: AGI is not possible even in 10 years
#50Earlier quoted context omitted.
>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 restr…
I'm very confused by your comment, but appreciate that you have precisely made my point. There are no "bets" with regard to these topics. How do you think a computer works? Do you seriously believe LLMs somehow escape the limitations of the machines they run on?
And what are the limitations of the machines they run on?
We're yet to find any process at all that can't be computed with a Turing machine.
Why do you expect that "intelligence" is a sudden outlier? Do you have an actual reason to expect that?