Keep in mind - this is not reaffirming HN's anti-AGI/extremely long timeline beliefs.
The article explicitly states that he thinks we will have an AI system that "Will be able to do your taxes" by 2028, and a system that could basically replace all white collar work by 2032.
I think an autonomous system that can reliably do your taxes with minimal to no input is already very very good, and 2032 being the benchmark time for being able to replace 90% - all white collar work is pretty much AGI, in my opinion.
Fwiw I think the fundamental problems he describes in the article that are AGI blockers are likely to be solved sooner than we think. Labs are not stupid enough to throw all their eggs and talent into the scaling basket, they are most definitely allocating resources to tackling problems like the ones described in the article, while putting the remaining resources into bottom line production (scale current model capibilities w/o expensive R&D and reduce serving/training cost).
When was OTS written again? That was effectively an expert system that could do your taxes and it was around at least ten years ago. It didn't even need transformers.
No one has a good benchmark for what AGI is. Already LLMs are more capable at most tasks than most random people off the street. I think at this point people keep asking about because they're trying to ask some deeper philosophical question like "when will it be human" but don't want to say that because it sounds silly.
> Already LLMs are more capable at most tasks than most random people off the street.
I cannot imagine having the narrow conceptualization of the universe of human tasks necessary to even be able to say this with a straight face, irrespective of ones qualitative assessment of how well LLMs do the things that they are capable of doing.
The article explicitly states that he thinks we will have an AI system that "Will be able to do your taxes" by 2028, and a system that could basically replace all white collar work by 2032.
I think an autonomous system that can reliably do your taxes with minimal to no input is already very very good, and 2032 being the benchmark time for being able to replace 90% - all white collar work is pretty much AGI, in my opinion.
Fwiw I think the fundamental problems he describes in the article that are AGI blockers are likely to be solved sooner than we think. Labs are not stupid enough to throw all their eggs and talent into the scaling basket, they are most definitely allocating resources to tackling problems like the ones described in the article, while putting the remaining resources into bottom line production (scale current model capibilities w/o expensive R&D and reduce serving/training cost).