筛选结果
115 篇排序
5:24EN → 简体中文Google I/O 2023:Bard、PaLM 2 与 Google 产品中的 AIMatthew Berman · Forward FutureMatthew Berman 回顾 Google 2023 年的 AI 发布,分析其重点改进现有产品的策略。
7:53EN → 简体中文HuggingGPT:用语言模型协调 AI 工具Matthew Berman · Forward FutureMatthew Berman 介绍一个研究系统:它以语言模型为控制器,将多模态任务分配给专门的模型。
1:29:31EN → 简体中文130,000 段遥操作演示:谷歌为机器人复刻的 GPT 打法主持 Nathan Labenz谷歌机器人团队的 Keerthana Gopalakrishnan 向 Nathan Labenz 讲述,RT-1、SayCan 和 PaLM-E 如何把语言模型的规模化,变成能进厨房干活的移动操作机器人。
1:21:20EN → 简体中文冻结眼睛和大脑,只训练视神经主持 Nathan LabenzJunnan Li 和 Dongxu Li 向 Nathan Labenz 讲述了 BLIP 如何清洗嘈杂的网页图像说明,以及 BLIP-2 如何在一块 A100 上、不到十天的时间里,把一个冻结的视觉模型接到一个冻结的语言模型上。
45:03EN → 简体中文Emad Mostaque 的赌注:开放的小模型,而非一个巨型大脑主持 Sarah Guo, Elad GilStability AI 创始人在 No Priors 节目上讲述,为什么基础模型应当是公共基础设施,为什么小模型能胜过巨型模型,以及这对媒体、医学和 AGI 意味着什么。
1:03:29ZH多模态论文串讲:BLIP、CoCa 与 BEiT-3从图文数据清理到统一预训练,梳理三种视觉语言模型的结构、目标函数与相互联系。
2:36:21EN → 简体中文笑容不等于快乐:Rana el Kaliouby 谈情感 AI 与共情危机嘉宾 Rana el Kaliouby · 主持 Lex FridmanAffectiva 创始人、Smart Eye 副 CEO 与 Lex Fridman 聊到,如何教机器读懂人脸、感知车内的驾驶员,以及她最自豪的是公司培养出来的人。
2:30:30EN → 简体中文成功第一步的谬误嘉宾 Ishan Misra · 主持 Lex Fridman伯克利的 Jitendra Malik 解释了计算机视觉为何仍然看起来很简单、全自动驾驶为何还遥遥无期,以及孩子知道而今天的网络不知道的是什么。
1:00:11EN → 简体中文Rosalind Picard:Clippy 从没见过你皱眉,问题就出在这里嘉宾 Rosalind Picard · 主持 Lex Fridman这位 MIT 教授给《情感计算》(Affective Computing)起了名字。她谈情绪识别、隐私、能探测癫痫发作的可穿戴设备,也谈为什么一个能摘下来的设备,比一个你看不见的摄像头更安全。
1:23:18ENFrom GPT-2 to GPT-3 Moments in Robotics: Six DeepMind Papers on Bridging Robots and the Internet主持 Nathan LabenzKeerthana Gopalakrishnan and Ted Xiao walk through RT-2, RT-X, RT-Trajectory, AutoRT, Learning to Learn Faster and PIVOT, and say what is still missing for general-purpose robots.
53:02ENAdobe's Firefly Bet: A Billion Beta Images, Creative Control, and Trust at Scale主持 Jacob EffronAdobe's Alexandre explains how Firefly moved from research to product, how Adobe balances creative control with generative speed, and why trust and feedback loops are central to its AI strategy.
1:53:14ENWorth Thousands, Priced at $20: Zvi Mowshowitz on OpenAI's Flurry, Gemini Bets, Deepfakes and a Compute Cap主持 Nathan LabenzZvi Mowshowitz and Nathan Labenz survey OpenAI's launch spree, AI pricing and bundling, data pollution, deepfakes, the reversal curse, calls to cap training compute, and Amazon's Anthropic deal.
1:03:24ENWhy Sora Bet on People, Not Just Pixels主持 Jacob EffronThe Sora team explains how a video model became a social creation network, what cameos revealed about human creativity, and why the next frontier is world simulation.
1:31:52ENFrom Phonemes to CTC: How Deep Learning Rebuilt Speech Recognition主持 Lex FridmanBaidu's Adam Coates walks through the traditional speech pipeline, the CTC-based end-to-end engine that replaced much of it, and what it takes to scale and deploy it.
1:45:55ENFrom Static Structures to Moving Molecules: Where AI for Protein Design Stands After AlphaFold 3主持 Nathan LabenzComputational biochemist Amelie Schreiber walks Nathan Labenz through six months of progress in structure prediction, molecular dynamics, peptide and antibody models, and early agent-driven design workflows.
1:02:57ENVirtual Biopsies in One Second: How a Seven-Year-Old CycleGAN Is Beating Newer Models in the Clinic主持 Nathan LabenzTanishq Mathew Abraham explains how deep learning turns label-free 3D tissue images into virtual H&E stains fast enough to guide tumor surgery.
23:54ENBeyond GPT-7: The Customization Toolkit, Meta's Open Source Bet and the Return of Consumer AI主持 Sarah Guo, Elad GilIn a host-only episode, the No Priors hosts map the six levers for 10x to 100x better AI, explain fine-tuning, RAG and AI feedback, and ask why consumer social is suddenly interesting again.
45:46ENGiving AI a Nervous System: Voice, Touch, and the Post-Keyboard Interface主持 Jacob EffronLiveKit's Russ explains how voice AI, multimodal chat, cloud browsers, and on-device models are reshaping how humans work with machines.
15:43ENInside RIDER: The Rugged Black Box Behind MIT's Large-Scale Driving Study嘉宾 MIT-AVT · 主持 Lex FridmanA walkthrough of the data-collection device MIT-AVT uses to record drivers and vehicles in semi-autonomous cars month after month.
1:13:40ENThe Long Tail, the World Model, and the 1995 Problem: Inside Waymo's Scaling Phase and Robotics' Missing Moment主持 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.
11:29ENWhy Tesla AI Day Was the Most Impressive Real-World AI Effort Lex Fridman Has Seen主持 Lex FridmanLex Fridman walks through the neural network, data annotation, Dojo and Tesla Bot announcements and what they say about solving real-world robotics.
2:02:13ENWiring Without a Vision: What OpenAI's and Google's Dueling Launches Really Signal主持 Nathan LabenzZvi Mowshowitz and Nathan Labenz unpack the week of GPT-4o and Google I/O, from rushed demos and AI companions to the big tech singularity and the exodus from OpenAI's safety team.
1:48:13ENRobotics Hits Its GPT-3.5 Moment: Inside Gemini Robotics, From Embodied Reasoning to Origami主持 Nathan LabenzGoogle DeepMind researchers Keerthana Gopalakrishnan and Ted Xiao explain how Gemini Robotics works, what it can and cannot do, and where the field goes next.
1:17:31ENImage AI Is Still at the GPT-2 Stage: Suhail Doshi on Building a Unified Vision Model主持 Nathan LabenzPlayground AI's founder explains why image generation has barely begun to deliver real utility, and why his team is betting 2024 on editing and a single model that can create, edit and understand pixels.
加载更多已显示 24 篇,共 115 篇









