TWiST 500 interviews with Cortical Labs, Turing, AND Mercor | E2159
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It's really important to Um benchmark um LMs. to figure out where they're good at Uh where are gaps in the models?
So that you can generate data that could help the LLMs get better at those specific tasks. One big challenge, Alex, that I see today in the overall Evaluation and benchmarking market. Is that the a lot of the evaluations are somewhat academic and somewhat synthetic. And don't connect to real world applications or real world use.
Ideally you want uh A G I to progress in a way Where the models get better at useful tasks. Yeah. This week in Startups is brought to you by
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