絞り込み結果
7 件並び順
2:59:44ENTwo Endangered Languages Broke Transformers. Nested Learning Gave Models a Sleep Button.ホスト Nathan LabenzGoogle researcher Ali Behrouz tells Nathan Labenz how stacking update frequencies — not just layers — and an offline sleep phase could give language models genuine continual learning.
1:01:14ENThe Model Eats the Scaffolding: How Google Plans to Ship Agents Everywhereホスト Nathan LabenzThree years after the leaked “no moat” memo, DeepMind’s Gemini leads walk through 3.5 Flash, Omni, and the shared agent harness now running through Google’s products.
44:34ENThe Cheaper Intelligence Gets, the More of It We'll Buyホスト Jacob EffronAmazon AGI Lab head David Luan on what DeepSeek actually meant, why next-token prediction is not enough, and why agents are still stuck on reliability.
26:28ENAPI prices fell 200x. The LLM table still is not set.ホスト Sarah Guo, Elad GilSarah Guo and Elad Gil, with no guest this week, argue over whether the language-model market has already consolidated — and why falling prices, five-person labs, and AMD’s shopping spree all cut against a simple ending.
42:08ENMeta Trained a 405B Teacher on 16,000 GPUs — Then Told the World to Distill ItTwo days after Llama 3.1 405B shipped, Meta's generative-AI product lead walks Sequoia through why the most expensive model in the family is free, and why he thinks the frontier itself is heading toward commodity.
1:12:15ENThe Open-Model Vibe Check: China, Containment, and the Data Moatホスト Jacob EffronJacob Effron and guests debate Chinese open-weight models, distillation, containment policy, the OpenAI–Hugging Face incident, and Cursor's data advantage.
1:13:40ENThe Long Tail, the World Model, and the 1995 Problem: Inside Waymo's Scaling Phase and Robotics' Missing Momentホスト Jacob EffronVincent, a distinguished engineer at Waymo, explains how foundation models became teachers for self-driving, why the long tail and causality are the real frontier, and where robotics still lacks its generalist proof point.






