Tao has a comment relevant to that question:

"I doubt that anything resembling genuine "artificial general intelligence" is within reach of current #AI tools. However, I think a weaker, but still quite valuable, type of "artificial general cleverness" is becoming a reality in various ways.

By "general cleverness", I mean the ability to solve broad classes of complex problems via somewhat ad hoc means. These means may be stochastic or the result of brute force computation; they may be ungrounded or fallible; and they may be either uninterpretable, or traceable back to similar tricks found in an AI's training data. So they would not qualify as the result of any true "intelligence". And yet, they can have a non-trivial success rate at achieving an increasingly wide spectrum of tasks, particularly when coupled with stringent verification procedures to filter out incorrect or unpromising approaches, at scales beyond what individual humans could achieve.

This results in the somewhat unintuitive combination of a technology that can be very useful and impressive, while simultaneously being fundamentally unsatisfying and disappointing - somewhat akin to how one's awe at an amazingly clever magic trick can dissipate (or transform to technical respect) once one learns how the trick was performed.

But perhaps this can be resolved by the realization that while cleverness and intelligence are somewhat correlated traits for humans, they are much more decoupled for AI tools (which are often optimized for cleverness), and viewing the current generation of such tools primarily as a stochastic generator of sometimes clever - and often useful - thoughts and outputs may be a more productive perspective when trying to use them to solve difficult problems."

This comment was made on Dec. 15, so I'm not entirely confident he still holds it?

https://mathstodon.xyz/@tao/115722360006034040

The "G" in "AGI" stands for "General".

While quickly I noticed that my pre-ChatGPT-3.5 use of the term was satisfied by ChatGPT-3.5, this turned out to be completely useless for 99% of discussions, as everyone turned out to have different boolean cut-offs for not only the generality, but also the artificiality and the intelligence, and also what counts as "intelligence" in the first place.

That everyone can pick a different boolean cut-off for each initial, means they're not really booleans.

Therefore, consider that this can't drive a car, so it's not fully general. And even those AI which can drive a car, can't do so in genuinely all conditions expected of a human, just most of them. Stuff like that.

AGI in its standard definition requires matching or surpassing humans on all cognitive tasks, not just in some, especially some where only handful of humans took a stab on.

This is very narrow AI, in a subdomain where results can be automatically verified (even within mathematics that isn't currently the case for most areas).