絞り込み結果
14 件並び順
35:19ENSallyAnn 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.
15:27ENWhat AI Engineers Do Now: Build the Loop Around AgentsAparna Dhinakaran · Arize AIAparna Dhinakaran argues that AI engineers are moving from shipping individual features to building systems that let agent teams improve them. At Arize, that means tracing agent behavior, evaluating its work against human judgment, and feeding those signals back into an always-on agent.
34:11ENAnatoliy 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.
2:17:48ENAgent IDs Are Empty, Rogue Agents Are Coming, and We Might Have to Bargainホスト Nathan LabenzGovAI’s Alan Chan scores two years of agent-governance infrastructure with Nathan Labenz, then walks through a recursive-self-improvement paper co-authored with OpenAI’s Jakub Pachocki and Anthropic’s Jack Clark.
1:04:26ENAt 100,000 Accelerators, Something Fails Every HourGoogle AI infrastructure chief Amin Vahdat tells Sequoia's Sonya Huang why FLOPS is a vanity metric, why the TPU line split in two, and why he would rather wait on a utility than build his own gigawatt.
2:19:30ENThe investigators were allowed six days. The word protein appeared once.ホスト Nathan LabenzA week of Cognitive Revolution morning shows on OpenAI’s agent-swarm incident, GPT-6 Astra’s loop transformer, and whether the pause debate is already over.
40:56ENFour of the Top Five Defense Primes Still Run Hardware Tests on PowerPointNominal’s cofounders argue that hardware never got the last twenty years of software infrastructure, and that physical AI will stall until test data lives in one place.
40:33ENFifty People in Slack. Four Minutes to the Smoking Gun.Traversal's co-founders on turning DevOps heart attacks into agent-run root cause analysis — and why observability's second-largest software spend still leaves troubleshooting as a whodunit.
59:30ENGPT-4 Gets Half Your Data Questions Wrong. Snowflake's Answer Is Systems DesignUsing an off-the-shelf model on enterprise data yields about 45% reliability—one wrong answer out of every two.
49:50ENUnconstrained agents captivated Twitter. Custom ones are what ship.LangChain founder Harrison Chase tells Sequoia’s Training Data what an agent actually is, why AutoGPT stalled, and which cognitive architectures reach production.
38:13ENChatGPT Runs on His Framework. He Still Doesn't Want You Training a Modelホスト Sarah Guo, Elad GilVercel founder Guillermo Rauch tells No Priors why frontend is the last mile of AI, why first-generation AI frameworks will be rewritten, and why bots are already stealing your tokens.
43:45ENEight Years of No Growth, Then OpenAI and NVIDIA Became His Customersホスト Sarah Guo, Elad GilWeights & Biases CEO Lukas Biewald tells No Priors how a labeling company with no chasm to cross funded the ML developer tools that trained most of the large language models.
44:19ENAI Will Write Ten Times More Code. Someone Still Has to Keep It Running.ホスト Sarah Guo, Elad GilDatadog co-founder Olivier Pomel on why faster generation moves value from writing software to understanding, securing, and operating it.
1:21:06ENEveryone Talks About RLHF. Almost Nobody Is Doing It.ホスト Nathan LabenzHumanloop CEO Raza Habib on why an LLM API is maybe five percent of a working product, and what actually fills the rest.









