The Ledger
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Chintala: George Hotz's TinyGrad requires major breakthroughs to match PyTorch
“There's no, like, I don't think, like, unless we have, like, great breakthroughs, like, George's vision is achievable, like, or, like, he should be thinking about a narrower problem, such as, I'm only gonna make this for, like, work for self-driving car con ne…”
Hotz: Tinygrad runs all ML models with only 25 primitive operations
“Tiny grad is, we are going to make a risk offset for all ML models. And yeah, it can run all ML models with basically 25 instead of the two 50 of XLA or PrimTorch. So about 10 X less complex.”
Hotz: Tinygrad runs OpenPilot in production 2x faster than Qualcomm's library
“TinyGrad is used to run the model in OpenPilot. Like right now, it's been live in production now for six months. And TinyGrad is about two X faster on the GPU than Qualcomm's library.”
Hotz: Tinygrad could replicate PyTorch's API in two engineer-months
“Replicating the PyTorch API. Is something I can do with a couple, you know, like an engineer month or two.”
Hotz: Tinygrad beats CoreML on ONNX tests and will soon pass ONNX Runtime
“We're below Onyx runtime, but we're beyond CoreML. So, like, that's, like, where we are in Onyx support now, but we will pass Onyx runtime soon, because it becomes very easy to add ops, because of how, like, you don't need to do anything at the lower levels.”