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When they say "the start", I think they mean the start of the current LLM era (circa 2017). The main story of this time has been a rejection of the idea that major conceptual breakthroughs and complex architectures are needed to achieve intelligence. Instead, it's better to focus on simple, general-purpose methods that can scale to massive amounts of data and compute (i.e. the Bitter Lesson [1]).

[1] http://www.incompleteideas.net/IncIdeas/BitterLesson.html



Oof ... to call other people's decades of research into directed machine learning "a colossal waste of researcher's time" is indeed a rather toxic point of view unsurprisingly causing a bitter reaction in scientists/researchers.

Even if his broader point might be valid (about the most fruitful directions in ML), calling something a "bitter lesson" while insulting a whole field of science is ... something.

Also as someone involved in early RL, he should know better.




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