OpenAI engineers: kernel optimization cut GPT-5.6 Sol serving cost by 20%
TheTuringPost · x · 2026-09-15
The Turing Post interviews OpenAI's Philippe Tillet and Matthew Ferrari, whose job is making AI cheaper and more accessible — increasingly with AI itself. Key points:
- Models now help find bottlenecks, optimize inference, and unlock experiments previously too complex to attempt
- A kernel improvement cut the end-to-end serving cost of GPT-5.6 Sol by 20%
- Every efficiency gain translates into broader product availability
The conversation also covers how AI is reshaping engineering, which optimizations are a waste of effort, and how well models understand the systems they optimize.
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