絞り込み結果
5 件並び順
35:19EN
AI Engineer· 2026年10月25日SallyAnn DeLucia: How to Write Your First AI EvalSallyAnn DeLucia · Arize AITurn an agent’s real traces into concrete pass/fail criteria, then build an LLM judge you can test, align with people, and run in production.
1:50:48EN
Y Combinator· 2026年10月24日Why Inference Matters 12× More Than TrainingFrançois Chaubard, Dan Fu, Jeff Morgan, Joe Fioti, Liangsheng Yin · Y CombinatorYC Paper Club walks the inference stack from an API request down to GPU kernels. Four talks from Together AI, Ollama, Luminal, and SGLang argue that serving quality, not just training FLOPs, is where most of the compute and the money now sit.
34:11EN
GOTO Conferences· 2026年10月23日Anatoliy Bilenko and Alberto Carretero: Making Database Protocols Reliable with Formal Methods and AIAnatoliy Bilenko, Alberto Carretero · CanonicalCanonical’s database engineers connect executable specifications, model-based tests, failure exploration, and reconstructed execution histories—and explain why none of these techniques proves a real system correct on its own.
56:49EN
Stanford AI Club· 2026年10月15日Alfred Lin on Building in the AI Era: The Diffusion Gap, Founder Conviction, and Fire and IceAlfred Lin, Jason Zhang, Tanvir Bhathal · Sequoia CapitalAt Stanford AI Club, Sequoia’s Alfred Lin explains where he sees opportunity in AI and why learning, human understanding, and operating discipline still shape enduring companies.
38:10EN
Google DeepMind· 2026年10月1日From deepfakes to DNA: how SynthID watermarks AIHannah Fry, Pushmeet Kohli, Jeremy Ratcliffe · Google DeepMindHannah Fry sits down with Pushmeet Kohli and Jeremy Ratcliffe to explain SynthID: a mathematical watermark now used on text, images and video, and being extended to protein sequences so DNA synthesis companies can tell AI-designed molecules from nature.