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by chasd00
845 days ago
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I wonder if it's a situation where the knowledge required to improve and enhance these models at a fundamental level vs just more data for testing or screwing around with system prompts is so deep and rare that a single person leaving an organization can have a gigantic impact on the overall trajectory of a startup. No amount of money will fix that problem if the skills required are that rare. Established large companies like Google, Facebook, etc have a much deeper bench of specialists than a startup I would assume and so can survive some people jumping ship. |
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Some people developed some intuition for it, but it's, well, random. We're evolving big things we don't really understand, and for reasons we don't really understand, some things evolve better than others. At some point, people starting getting feelings in their gut that some "architectures" worked better for vision than NLP, and things diverged. There continues to be queasy-gut intuition, but when you read all the papers, if you cut through all the hairy math language, it's a lot of voodoo and throwing darts at a board.
I think it's much more the same problem you'd have at any shop, where the smartest people want to work for FAANG / sexy startups / elite universities, etc., and the bottom end of the market just wants a job, and lands with lower-tier employers. Talent naturally consolidates. At the same time, org culture, strategy, and leadership can have a huge impact too.