"I remember when AGI meant being able to generalize knowledge over problems not specifically accounted for in the algorithm… "
So do we have that?
As far as I know, we just have very, very large algorithms (to use your terminology). Give it any problem not in the training data and it fails.
Same goes for most animals and humans, the vast majority of the time. We expect consistent savant level performance or it’s not “AGI” if humans were good at actual information synthesis, Einstein and Tom Robbins would be everyone’s next door neighbors.
As a sounding board and source of generally useful information, even my small locally hosted models generally outperform a substantial slice of the population.
We all know people we would not ask anything that mattered, because their ideas and opinions are typically not insightful or informative. Conversing with a 24b model is likely to have higher utility. Do these people then not exhibit “general intelligence”? I really think we generally accept pattern matching and next-token ramblings, hallucinations, and rampant failures of reasoning in stride from people, while applying a much, much higher bar to LLMs.
To me this makes no sense, because LLMs are compilations of human culture and their only functionality is to replicate human behavior. I think on average they do a pretty good job vs a random sampling of people, most of the time.
I guess we see this IRL when we internally label some people as “NPC’s”.
"As a sounding board and source of generally useful information, even my small locally hosted models generally outperform a substantial slice of the population."
So does my local copy of Wikipedia.
But the lines do get blurry and many real humans indeed seem no more than stochastical parrots pretending understanding.
So do we have that? As far as I know, we just have very, very large algorithms (to use your terminology). Give it any problem not in the training data and it fails.