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Modular’s bet to break out of the Matrix (Democratizing AI Compute, Part 10)

May 8, 2025

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Chris Lattner

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Democratizing AI Compute, Part 9: Why Do HW Companies Struggle to Build AI Software?

April 22, 2025

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Chris Lattner

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What about the MLIR compiler infrastructure? (Democratizing AI Compute, Part 8)

April 8, 2025

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Chris Lattner

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What about Triton and Python eDSLs? (Democratizing AI Compute, Part 7)

In this post, we’ll break down how Python eDSLs work, their strengths and weaknesses, and take a close look at Triton.

March 26, 2025

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Chris Lattner

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Democratizing AI Compute, Part 6: What about AI compilers (TVM and XLA)?

March 12, 2025

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Chris Lattner

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What about OpenCL and CUDA C++ alternatives? (Democratizing AI Compute, Part 5)

March 5, 2025

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Chris Lattner

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CUDA is the incumbent, but is it any good? (Democratizing AI Compute, Part 4)

Answering the question of whether CUDA is “good” is much trickier than it sounds.

February 20, 2025

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Chris Lattner

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How did CUDA succeed? (Democratizing AI Compute, Part 3)

If we as an ecosystem hope to make progress, we need to understand how the CUDA software empire became so dominant.

February 12, 2025

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Chris Lattner

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What exactly is “CUDA”? (Democratizing AI Compute, Part 2)

February 5, 2025

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Chris Lattner

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DeepSeek’s Impact on AI (Democratizing AI Compute, Part 1)

Part 1 of an article that explores the future of hardware acceleration for AI beyond CUDA, framed in the context of the release of DeepSeek

January 30, 2025

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Chris Lattner

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