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28 August
10 August
30 July
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Their words
Yeah, I mean it's a little different, but I think uh you're going to see more and more uh uh high performance and um low energy uh inference hardware systems because I think everyone is now realizing that inference is the key to making you know these agent-based systems be available to more and more people and that latency is really important and that specialization of the hardware is a really key way you can make uh things that are more energy efficient and lower latency than more general purpose uh computational devices like say GPUs or TPUs
18 June
27 May
From one piece Building OpenCode with Dax Raad 2 beliefs, in the piece's order there
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Their words
cuz because we rent GPUs at scale to run the models and we still use middleman by the way. So we're not like going all the way down to the down to the floor. Even for us there are some models the sticker price and the cost to us there's like an 80% margin in there.
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Their words
The demand for inference is growing. So, like I don't think it's linearly growing. I think it might even be exponentially growing. But we haven't made our production of GPUs grow exponentially. That's like kind of a linear process. So as those lines intersect, there's going to be uh tightening.
10 February
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Their words
The economics of orbital “datacenters” or essentially glorified Starlink satellites with a bunch of GPUs attached are likely to be even better than Starlink.
Space AI: I guess we’re doing Moon factories nowcaseyhandmer.wordpress.com
1 February
8 June 2025
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korrents.com
Graphics chips have far more room for future performance gains than CPUs, which are nearing physical limits.Their words
GPUs are not nearly as restricted in their future progress as CPUs which are far more constrained in how they can physically improve (compiler-driven ILP only goes so far).
3 February 2025
From one piece DeepSeek, China, OpenAI, NVIDIA, xAI, TSMC, Stargate, and AI Megaclusters | Lex Fridman Podcast #459 2 beliefs, in the piece's order there
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Their words
So, Japan has a law which you're allowed to train on any training data and copyrights don't apply if you want to train a model, A. B, Japan has 9 gigawatts of curtailed nuclear power. C, Japan is allowed under the AI diffusion rule to import as many GPUs as they'd like.
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Their words
One is ByteDance, arguably is the largest smuggler of GPUs for China. China's not supposed to have GPUs. ByteDance has over 500,000 GPUs. Why? Because they're all rented from companies around the world.
29 June 2023
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Their words
It’s always harder to write software for more specialized hardware. A GPU is pretty generic. If you can’t write an in Nvidia stack, there’s no way you can write a stack for your chip. My approach with Tinygrad is first write a performant NVIDIA stack.
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