2 ms·

>I get it. You don't feel ownership over someone else's AI. You don't feel involved, you don't feel like you have agency. You don't _have_ ownership of someone

by SCHiM 2mo ago

>I get it. You don't feel ownership over someone else's AI. You don't feel involved, you don't feel like you have agency. You don't _have_ ownership of someone else's ai, and that comes with real risks. Security risks, privacy risks, business risk. They might rug pull you, they might charge you more, or like atrophic, silently corrupt the answers, or code... The labs are happy to jump on any emergent capability the scaling and training impart: generate prose, teach you things, cyber security, design, code, etc. Do you really think that the frontier labs won't turn a popular capability, or trend they notice, into a first party tool if the ROI seems there? If it's your own private ai in your datacenter, you can keep it all secret, and not lose your business. On the bitter lesson you're right of course:), wish I had a super computer to just scale that instead.

jiggawatts 2mo ago
It doesn't have to be "externally hosted, proprietary AI model"! The argument is against "self-assembled small AI pieces" versus frontier monolithic models. A) You can always self-host something like Kimi, DeepSeek, or GLM. B) Just because you use a specific proprietary AI for programming doesn't actually bind you to that provider in any meaningful way. The authored code remains even if you stop paying them! Of course, if you use AI as an active component in some sort of service, then the EULA, rug-pulls, etc... suddenly start to matter. That's a different story.
- SCHiM 2mo ago
  Anthropic* I think I agree with the bitter lesson, but I wish I weren't :) > A) You can always self-host something like Kimi, DeepSeek, or GLM. I mean, one could rent-a-box for, like, 10$$ per hour? Agentic loop development gets really expensive at scale with larger models, like, if you want to A/B test two tool schemas to see which works better, and you run 100 benchmarks... But why are you so convinced the bitter lesson is true, and it's not just a temporary lead? Proper agent loops and RLVR are like, 3 years old at this point? At some point, right, the compute can't scale it out further? And at _that_ point the lead position might go back to: highest compute + smartest designed smarts. Against my somewhat better judgement I'm currently "assembling small AI pieces" :(, for lack of access to unrestricted models for offensive security work and, ehh, funds. It's _okay_ so far, I'm running private benchmarks and look at the trajectories. To be perfectly honest, qwen is _really_ doing well, finishing quite complex chains without a lot of smarts in the prompt. Just "Go pwn {server}, use these {tools}". But, there are some smarts embedded in those tools. Helpful errors, retries, benchmarked/handy representation. Strict validation of what the model tries to do, etc. > The authored code remains even if you stop paying them! This is true, but my point is that they will outcompete you if you happen to stumble on something that actually makes good money using LLMs and becomes popular. Obviously, if you don't then they won't. > Of course, if you use AI as an active component in some sort of service, then the EULA, rug-pulls, etc... suddenly start to matter. That's a different story. That's the plan hehe

by SCHiM 2mo ago

jiggawatts 2mo ago

It doesn't have to be "externally hosted, proprietary AI model"! The argument is against "self-assembled small AI pieces" versus frontier monolithic models. A) You can always self-host something like Kimi, DeepSeek, or GLM. B) Just because you use a specific proprietary AI for programming doesn't actually bind you to that provider in any meaningful way. The authored code remains even if you stop paying them! Of course, if you use AI as an active component in some sort of service, then the EULA, rug-pulls, etc... suddenly start to matter. That's a different story.

SCHiM 2mo ago
Anthropic* I think I agree with the bitter lesson, but I wish I weren't :) > A) You can always self-host something like Kimi, DeepSeek, or GLM. I mean, one could rent-a-box for, like, 10$$ per hour? Agentic loop development gets really expensive at scale with larger models, like, if you want to A/B test two tool schemas to see which works better, and you run 100 benchmarks... But why are you so convinced the bitter lesson is true, and it's not just a temporary lead? Proper agent loops and RLVR are like, 3 years old at this point? At some point, right, the compute can't scale it out further? And at _that_ point the lead position might go back to: highest compute + smartest designed smarts. Against my somewhat better judgement I'm currently "assembling small AI pieces" :(, for lack of access to unrestricted models for offensive security work and, ehh, funds. It's _okay_ so far, I'm running private benchmarks and look at the trajectories. To be perfectly honest, qwen is _really_ doing well, finishing quite complex chains without a lot of smarts in the prompt. Just "Go pwn {server}, use these {tools}". But, there are some smarts embedded in those tools. Helpful errors, retries, benchmarked/handy representation. Strict validation of what the model tries to do, etc. > The authored code remains even if you stop paying them! This is true, but my point is that they will outcompete you if you happen to stumble on something that actually makes good money using LLMs and becomes popular. Obviously, if you don't then they won't. > Of course, if you use AI as an active component in some sort of service, then the EULA, rug-pulls, etc... suddenly start to matter. That's a different story. That's the plan hehe