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GPU potential extends beyond standard math machine applications
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Flapping Airplanes co-founder @aidanmantine explains why treating GPUs as "just a math machine" wastes their potential: "We look at GPUs and we say, how do you go under the floorboards? We don’t use Torch. We don’t use NVIDIA’s normal CUDA runtime stuff. We don’t use NCCL. We basically have built everything from scratch." "This means we can do some really crazy stuff like have your experimental training models run at the highest level of a production inference stack at a big lab. The systems…
MTS@MTSlive2d ago
FULL INTERVIEW: Flapping Airplanes just raised a $1B Series A after rebuilding the GPU stack from scratch. Co-founder Aidan Smith says they don’t even use Torch, NCCL or CUDA’s normal runtime. One kernel on one B200 can now train a model, serve inference and play Doom at the same time. @aidanmantine, Thiel Fellow and 3-year Neuralink alum, co-founded @flappyairplanes. He joined @sophiadew and @theojaffee to break down why AI needs to learn more like the brain, how they rebuilt the GPU stack, and who they hire: 00:30 where the name Flapping Airplanes comes from 02:04 why they bet on data efficiency 03:07 what Neuralink taught him about AI 04:27 how slow your brain actually is 06:06 why not just emulate the whole brain 08:40 why they rebuilt the GPU stack from scratch 10:33 compute overhang and safety 12:56 can a neo lab win if the big labs hit RSI first 14:27 what ML research looks like when no one writes code 15:40 why DNA, robotics and trading are data-starved 18:41 how they hire in the AI talent wars 21:17 the models they might ship first
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