This blog post series from Chris Lattner extensively examines CUDA's pervasive dominance in AI compute, detailing its evolution from a graphics processor to a layered software platform integral to NVIDIA's success, while also highlighting the challenges and complexities it presents to developers and alternative hardware vendors. The articles critically assess various attempts to democratize AI compute, including OpenCL, TVM, XLA, and MLIR, explaining why these alternatives largely failed to dislodge CUDA due to fragmentation, misaligned incentives, and a lack of unified vision. Ultimately, the texts introduce Modular's approach to addressing these issues through its Mojo language, MAX framework, and Mammoth cluster management system, aiming to provide a portable, performant, and programmable solution for the rapidly evolving Generative AI landscape.Source:https://www.modular.com/blog/democratizing-compute-part-1-deepseeks-impact-on-ai

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