Asking for a friend who’s working on a startup around this general space: do you think it’s better to go niche, focusing on agents for a specific type of application or a specific language/ecosystem, or is that effectively “killing the startup” by limiting market size too soon?
Another question that came up in conversations with them: there might be value in offering a nonscalable, high-touch service, where you build and maintain customized agents tailored to a client’s specific codebase on a periodic basis.
I think it's probably a bad idea to do an "AI looking for vulnerabilities" startup, since the frontier labs have all basically declared that they believe that's a feature of a coding agent and not a standalone product.
Sidenote: I didn’t know anything about Freestyle Chess before reading this, so I checked Wikipedia first[1]. Interestingly, the randomized nature of the format, its defining feature, isn’t strongly emphasized upfront, which may make it less immediately clear to newcomers.
Possibly, but that assumes continuity. New math and algorithmic breakthroughs could make much of today’s AI stack legacy, reshuffling both costs and winners.
Understandable, unfortunately I haven't found a better method than BYOK for a free app. If you'd like to try it, you can generate a new key, test it for 10 minutes, and then delete it. Alternatively, you can watch a video of the generation process: https://old.reddit.com/r/StableDiffusion/comments/1qsuu58/ex...
What's striking is the sheer scale of Epstein's and Maxwell's scheduling and access. The source material makes it hard to even imagine how two people could sustain that many meetings/parties/dinners/victims, across so many places, with such high-profile figures. And, how those figures consistently found the time to meet them.
Another question that came up in conversations with them: there might be value in offering a nonscalable, high-touch service, where you build and maintain customized agents tailored to a client’s specific codebase on a periodic basis.
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