The Bitter Lesson is very popular right now. It seems true right now. It’s having its moment right now. That doesn’t actually mean it’s axiomatically true.

Commenter below gets it absolutely correct: stockfish, which runs on your 5 year old phone, is dramatically better at chess than Fable. Like, so much better that it’s not even remotely comparable. The theory of the Bitter Lesson, and it’s only a theory, is that LLMs could eventually outperform stockfish. It’s not true today and it remains to be seen whether it will ever be true. For now, specialized models are absolutely better at specialized tasks.

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mikepurvis 14 minutes ago | parent | next [-]

But isn't that really just about giving "front end" models more access to specialized tool libraries, which include models tuned to specific tasks? Like the first model says ah, we're being asked to code something, oh and we've been provided with some example code, let me invoke a tool call to my model the recognizes many languages, that model says that we're looking at ocaml. Okay, I better pass this off to my ocaml model which will decipher the supplied code and make a plan for what we do about the user's intent. The ocaml model recognizes that there are tests in the supplied code, let's have the special testing model have a look at the testing strategy and see how that fits in with what we just implemented, etc etc.

And perhaps at the end it all gets a single pass by a god-tier model for overall sanity and congruence, but the actual work, planning, coordination, and even user interaction was done by cheaper and faster agents of much more limited capability.

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Evidlo 2 hours ago | parent | prev | next [-]

This seems really backwards. The Bitter Lesson is all about large data-based approaches vs hand-crafted ones, it doesn't say anything about language models not trained specifically for chess.

I can't find the comment you're referring to, but the latest versions of stockfish are based on neural networks trained on millions of games, so if anything the Bitter Lesson turned out true here.

	▲	nickysielicki 30 minutes ago \| parent [-]
		The conclusion of the bitter lesson would be that a large language model trained on chess commentary as well as being trained on millions of chess games would outperform stockfish which is only trained on millions of chess games. There’s no evidence at this point that this is true.

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Animats 2 hours ago | parent | prev | next [-]

Good point.

Dumb AIs are needed for customer service. Most of that industry is still at "press 1 for sales, 2 for billing..." and needs something that will run locally on a 1U server.

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PEe9bB7D 2 hours ago | parent | prev [-]

Maybe depends on how you ask it? Directly, or let it write a chess program? I think the latter can yield way better results.