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It is astonishing to see how poorly inverters understand AI hardware. Google's TPU is not going to take NVIDIAs market. If anything, it will expand the whole ecosystem. I cannot: 1. Own a TPU (at any cost) 2. Put a TPU in a robot 3. Put a TPU in a car 4. Put a TPU in a custom rack 5. Design a custom board for a TPU 6. Run my own OS with a TPU 7. Develop code on a 6 year old TPU I got for $100 8. Test optimizations on my own hardware 9. Run ANY model on a TPU (they have to be modified/customized) 10. Can't even see the actual hardware specs for a TPU. The TPU will help Google lower their costs, but it is a completely different, super specialized product and market than what NVIDIA sells.
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Ilya on research taste: “One thing that guides me personally is an aesthetic of how AI should be by thinking about how people are. There's no room for ugliness. It's just beauty, simplicity, elegance, with correct inspiration from the brain. The more they are present, the more confident you can be in a top-down belief. The top-down belief is the thing that sustains you when the experiments contradict you. Because if you just trust the data all the time, sometimes you can be doing a correct thing, but there's a bug. How do you know if you should keep debugging or you conclude it's the wrong direction? You must say that things have to be this way, therefore we've got to keep going. That's the top-down belief, and it's based on this multifaceted beauty and inspiration by the brain.”
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I build sane open-source RL tools. MIT PhD, creator of Neural MMO and founder of PufferAI. DM for business: non-LLM sim engineering, RL R&D, infra & support.
German cities seem to learn the hard way how important businesses are for… everything.
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