Results
201 articlesSort
9:58EN
Matthew Berman· Apr 26, 2023HuggingChat’s 2023 Debut: Testing Writing, Reasoning and Python CodeMatthew Berman · Forward FutureMatthew Berman tries the early OpenAssistant-powered HuggingChat on writing, arithmetic, logic and a Snake game, then compares a few outputs with GPT-3.5 and GPT-4. The results illustrate both promise and limitations in this small historical test.
53:37EN
No Priors: AI, Machine Learning, Tech, & Startups· Mar 9, 2023Podcast · 2 speakers30 models, 42 scenarios, 7 metrics: Percy Liang's public checkup for language modelsHost Sarah Guo, Elad GilA PubMed-only model once led the U.S. medical licensing exam — until a system roughly 200 times larger overtook it.
2:34:20EN
Lex Fridman· Aug 30, 2020Podcast · 2 speakersIntelligence Is How Efficiently You Acquire Skills You Were Not Prepared ForGuest François Chollet · Host Lex FridmanFrançois Chollet tells Lex Fridman why skill is not intelligence, why GPT-3 is still pattern matching, and why a grid puzzle called ARC still separates children from machines.
1:49:51ENLex Fridman· Jun 27, 2020Podcast · 2 speakersThe Idea Once Called a Devolution Now Powers Almost Every New ChipGuest David Patterson · Host Lex FridmanTuring Award winner David Patterson talks with Lex Fridman about RISC, RAID, Moore's Law, open hardware, and why chips without a software stack die.
16:03ENLex Fridman· Feb 22, 2020Podcast · 2 speakersQuantum Supremacy Is a Well-Defined Speedup, Not a Useful TaskGuest Scott Aaronson · Host Lex FridmanScott Aaronson explains what Google's 53-qubit experiment actually demonstrated, how it was verified, and why complexity theory can offer evidence but not proof against classical spoofing.
57:57EN
Jane Street· May 8, 2019Sebastian Funk on a Fast, Safe and Maintainable Packet ProcessorSebastian Funk · Jane StreetA single-core market-data case study shows how latency targets, allocation control and generated code can coexist with high-level abstractions.
11:11ENLex FridmanPodcast · 2 speakersYann LeCun on Benchmarks, Interactive Environments, and Why Human Intelligence Is Not GeneralGuest Yann Lecun · Host 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"PodcastHuman-Level but Not Human-Like: A GPT-4 Red Teamer on What He Saw Behind the MaskHost 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 FridmanPodcast · 2 speakersTalking for 20 Minutes: How the Alexa Prize Turns Real Customers into a Testbed for Conversational AIGuest Rohit Prasad · Host 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 FridmanPodcastAlphaFold 2 and the Protein-Folding Breakthrough: Why Lex Fridman Calls It a Landmark for AI and BiologyHost 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"PodcastGemini 2.0 Flash Goes to Production: Pricing, Model Lineup and What Developers Should Build NextHost 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 FridmanPodcast · 2 speakersCan Machines Think? A Guided Tour of Turing's Test, Its Critics and Its SuccessorsGuest Turing Test · Host 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"PodcastOne Set of Weights, Fourteen Medical Tasks: Inside Google's Multimodal Med-PaLM MHost 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.