>This article would be 100% correct if it came out 1 year ago, 75% correct 9 months ago, 50% correct 3 months ago and it's probably 25% correct now if not less.
Feels like I read comment similar to this one each year since 2023.
Feels like I read comment similar to this one each year since 2023.
That's when the models started to be coherent enough for real work.
They still fuck up, but it does not feel the code was written by drunk interns anymore.
This reflects my own experience with these models. It's not a matter of inflection point if you ask me, it's a matter of accruing capabilities last year the output was not up to my standards 98% of the time, now it looks more like 30% of the time.
I am sure next year models will be better, but the point where the models begun being good enough to start using seriously for my use cases has now passed.