Five Years of tinygrad: Reflections on Building an Open-Source Deep Learning Framework
By
iyaja
The bagel they save for the regulars. Don't skim, savour.
Summary
The article reflects on five years of development of tinygrad, an open-source deep learning framework. The author discusses the project's evolution from its first commit in 2020, the company's growth to 6 people, and the 18,935-line codebase. The piece emphasizes the importance of building a complete software stack before hardware development, arguing that software sovereignty is key to competing with NVIDIA. The author shares personal reflections on the long-term commitment required for such projects and the strategic approach of focusing on software first rather than immediately developing chips.
Key quotes
· 4 pulledI have spent 5 years of my life working on 18,935 lines, and now many others have put years in as well. And there's probably 5 more years to go.
Only a fool begins by taping out a chip; it's expensive and not the hard part.
Once you have a fully sovereign software stack capable of training SOTA models, the chip is so easy.
But this is the right process to compete with NVIDIA.
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