I used to have the same opinion for many years. Then generative AI became good. Good enough for me to use it as a daily assistant. So good it scared me and led

I used to have the same opinion for many years. Then generative AI became good. Good enough for me to use it as a daily assistant. So good it scared me and led me to rethink my position. I have missed one crucial thing: Big enough changes in quantity do lead new qualities as well. Training models with insane amounts of data was the necessary step to finally make the qualitative leap into developing models that were practical for mainstream use. One of the big things holding back AI research has always been trying to be too clever. This article sums it up perfectly: > The biggest lesson that can be read from 70 years of AI research is that general methods that leverage computation are ultimately the most effective, and by a large margin. http://www.incompleteideas.net/IncIdeas/BitterLesson.html http://www.incompleteideas.net/IncIdeas/BitterLesson.html