zlacker

>>davidb+(OP)
Ilya booted him https://twitter.com/karaswisher/status/1725702501435941294

>>johnwh+Uc1
Jeremy Howard called ngmi on OpenAI during the Vanishing Gradients podcast yesterday, and Ilya has probably been thinking the same: LLM is a dead-end and not the path to AGI.

https://twitter.com/HamelHusain/status/1725655686913392933

>>dwd+zL1
Did we ever think LLMs were a path to AGI...? AGI is friggin hard, I don't know why folks keep getting fooled whenever a bot writes a coherent sentence.

>>erhaet+1O1
It's mostly a thing among the youngs I feel. Anybody old enough to remember the same 'OMG its going to change the world' cycles around AI every two or three decades knows better. The field is not actually advancing. It still wrestles with the same fundamental problems they were doing in the early 60s. The only change is external, where computer power gains and data set size increases allow brute forcing problems.

>>Rugged+9P1
I'd say the biggest change is the quantity of available CATEGORIZED data. Tagged images and what not has done a ton to help the field.

Further there are some hybrid chips which might help increase computing power specifically for the matrix math that all these systems work on.

But yeah, none of this is making what people talk about when they say AGI. Just like how some tech cult people felt that Level 5 self driving was around the corner, even with all the evidence to the contrary.

The self driving we have (or really, assisted cruise control) IS impressive, and leagues ahead of what we could do even a decade or two ago, but the gulf between that, and the goal, is similar to GPT and AGI in my eyes.

There are a lot of fundamental problems we still don't have answers to. We've just gotten a lot better at doing what we already did, and getting more conformity on how.