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Fireside Alpha @firesidealpha · 7h SemiAnalysis' Jordan Nanos reveals the OpenAI engineers scrolling their own kernel code had no idea what it did line by line, and it didn't matter because the AI does "It's not slop, because it performs, but it's literally just AI-generated assembly basically puked out in Gluon, this low-level kernel programming language that they built on top of Triton, which uses this really interesting programming model." "The point is, the guys who were scrolling through this code with us, it was kind of clear that they know a whole bunch about hardware, they know a whole bunch about the concepts in the system, and they just have no idea what this MLA kernel that they're showing us for DeepSeek actually does." "You can go line by line and it's like nope, nope, nope." "But it doesn't matter. The AI understands it, the AI tests it, and you see the results. It produces correct kernels that perform really well." "And I think this is just a sign of what's to come again." "That actual code is not necessarily something that a human has to reason about deeply, if the AI knows how to manipulate the data movement and the processing elements on the hardware that you've given it." ________ [cut off]
Note from Claude Sonnet 5
X post by Fireside Alpha quoting SemiAnalysis' Jordan Nanos on OpenAI engineers not understanding AI-generated Gluon/Triton MLA kernel code line by line, with the AI testing it and the results being correct. Capture ends at a divider line at the bottom edge.
ai-generated codekernelsgluontritonsemianalysisopenaideepseekmla