筛选结果
208 篇排序
11:11EN
Lex Fridman播客 · 2 人对谈Yann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not General嘉宾 Yann Lecun · 主持 Lex FridmanIn a 2019 clip, LeCun defends benchmarks as a test of AI claims, explains why interactive environments break the usual train-test protocol, and argues that "general intelligence" is a misnomer.
1:22:57EN
Cognitive Revolution "How AI Changes Everything"播客Human-Level but Not Human-Like: A GPT-4 Red Teamer on What He Saw Behind the Mask主持 Nathan LabenzNathan Labenz recounts two months of full-time testing of an early GPT-4, from the AI doctor of his dreams to a model that would plan assassinations on request.
14:41ENLex Fridman播客 · 2 人对谈Talking for 20 Minutes: How the Alexa Prize Turns Real Customers into a Testbed for Conversational AI嘉宾 Rohit Prasad · 主持 Lex FridmanRohit Prasad, head scientist of Amazon Alexa, explains the Alexa Prize grand challenge, how it is judged and why true conversation still needs reasoning.
16:41ENLex Fridman播客AlphaFold 2 and the Protein-Folding Breakthrough: Why Lex Fridman Calls It a Landmark for AI and Biology主持 Lex FridmanA quick explainer on DeepMind's CASP14 result, how protein folding works, how AlphaFold 1 and 2 likely differ, and what the advance could unlock.
57:21ENCognitive Revolution "How AI Changes Everything"播客Gemini 2.0 Flash Goes to Production: Pricing, Model Lineup and What Developers Should Build Next主持 Nathan LabenzGoogle DeepMind's Logan Kilpatrick walks through launch-day Gemini 2.0 releases, rate limits, model naming, and where he sees startup opportunities.
1:00:25ENLex Fridman播客 · 2 人对谈Can Machines Think? A Guided Tour of Turing's Test, Its Critics and Its Successors嘉宾 Turing Test · 主持 Lex FridmanLex Fridman walks through Alan Turing's 1950 paper, the objections to it, and the benchmarks that have tried to replace or extend the imitation game.
1:22:17ENCognitive Revolution "How AI Changes Everything"播客One Set of Weights, Fourteen Medical Tasks: Inside Google's Multimodal Med-PaLM M主持 Nathan LabenzVivek Natarajan and Tao Tu explain how Google built a single generalist biomedical model that reads images, genomics and text, and what it will take to put it in front of patients.