Inference optimization

Jul 11, 2026

State of the Union: Why Local, Why Now — NVIDIA, Osmantic, Roboflow, EXO Labs, @matthew_berman

This panel discussion explores the inflection point of Local AI, driven by advanced models, improved hardware, and a robust ecosystem. Experts discuss how this shift addresses critical concerns around privacy, cost, sovereignty, and resilience, emphasizing the pivotal role of open-source AI and specialized models. They delve into technical optimizations, the evolution from generalized to specialized AI, and the challenges of making local AI accessible and performant for both enterprise and individual users.

May 26, 2026

Frontier AI at Home — Alex Cheema, EXO Labs

Alex Cheema from EXO Labs explores the path to a 100x improvement in the price-performance of running frontier AI models locally. The talk covers full-stack optimization strategies, including kernel fusion for a 30% performance boost, RDMA for scalable tensor parallelism, and a novel approach of splitting prefill and decode phases across heterogeneous hardware (e.g., an RTX GPU and Mac Studios) to significantly speed up large-prompt inference.