Comment by joefourier
3 days ago
We are already at AGI. I don’t know how you can argue that LLMs don’t meet the definition of general artificial intelligence, as opposed to narrow AI like chess engines, image classifiers, AlphaGo or self driving cars, which are trained with one objective and cannot even possibly be applied to any other task.
People have just moved the goalposts, imagine explaining Opus 4.6’s capabilities to someone even 10 years ago, it would definitely have been called AGI.
I highly doubt there will be a point where everyone will agree that we’ve achieved ASI, there will always be a Gary Marcus type finding some edge case where it performs poorly.
> People have just moved the goalposts
Yes, I agree. Just not in the direction you’re claiming.
> imagine explaining Opus 4.6’s capabilities to someone even 10 years ago, it would definitely have been called AGI.
No, it would have been called AI. A decade ago most people were not familiar with AGI as a term, that just got popularised because AI was taken over to be basically what we used to call ML.
> No, it would have been called AI. A decade ago most people were not familiar with AGI as a term, that just got popularised because AI was taken over to be basically what we used to call ML.
Define "most people", I don't think the average user of ChatGPT is familiar with the term AGI even now, but it's been used in the AI/ML community for multiple decades. I remember reading about the distinction between general and narrow AI around 2010 as an enthusiast. "Strong" vs "weak" AI were also used although with essentially the same definition, although they're less common terms nowadays.
> Define "most people"
The majority of individuals. Pick a random sample and ask. This is not a trick term.