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How is Modular Democratizing AI Compute? (Democratizing AI Compute, Part 11)

Given time, budget, and expertise from a team of veterans who’ve built this stack before, Modular set out to solve one of the defining challenges of our era: how to Democratize AI Compute. But what does that really mean—and how does it all add up?

June 20, 2025

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Chris Lattner

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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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Why do HW companies struggle to build AI software? (Democratizing AI Compute, Part 9)

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

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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