While Gary is very bearish on AI, I think there's some truth to his claims here though I disagree with how he got there. The problem I see with AI and AGI is no

While Gary is very bearish on AI, I think there's some truth to his claims here though I disagree with how he got there. The problem I see with AI and AGI is not so much a technical problem as an economic one. If we keep down our current trajectory of pouring billions on top of billions into AI then yes I think it would be plausible that in the next 10-20 years we will have a class of models that are "pseudo-AGI", that is we may not achieve true AGI but the models are going to be so good that it could well be considered AGI in many use cases. But the problem I see is that this will require exponential growth and exponential spending and the wheels are already starting to catch fire. Currently we see many circular investments and unfortunately I see it as the beginning of the AI bubble bursting. The root of the issue is simply that these AI companies are spending 10x-100x or more on research than they bring in with revenue, OpenAI is spending ~$300B on AI training and infra while their revenue is ~$12B. At some point the money and patience from investors is going to run out and that is going to happen long before we reach AGI. And I have to hand it to Sam Altman and others in the space that made the audacious bet that they could get to AGI before the music stops but from where I'm standing the song is about to come to an end and AGI is still very much in the future. Once the VC dollars dry up the timeline for AGI will likely get pushed another 20-30 years and that's assuming that there aren't other insurmountable technical hurdles along the way.