llm-inference

David Abitbol runs AI operations at Revolut, a European digital bank with about 80 million customers. In under twelve minutes at AI Engineer New York he covers how Revolut moved most of its coding-agent traffic from frontier APIs to a self-hosted open model, and he brings numbers: engineer lead times from a 2,000-person sample, GPU count, latency targets, cost per million tokens, and the tuning changes that mattered. It’s one of the more concrete inference-economics talks this year....

Weekly Paper Notes — one of the top picks from the 2026-08-15 CS paper digest. Area: Operating Systems / Systems. Authors: Yuan Si (University of Waterloo), Yufeng Lin (Independent), Daming Li (Independent), Jialu Zhang (University of Waterloo, corresponding) arXiv: 2608.12103 · PDF TL;DR A trillion-parameter mixture-of-experts model routes each token through a small, input-dependent slice of its weights — in the production model studied here, an accepted token costs on average 1585 expert reads of 17....