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Matthew Berman· 12 jul 2023PoisonGPT: A Demonstration of Model Supply-Chain RiskMatthew Berman · Forward FutureMatthew Berman discusses Mithril Security’s 2023 demonstration of an edited GPT-J model and a misleading repository name. The experiment illustrates a supply-chain risk, not a breach of the original model provider.
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20VC with Harry Stebbings· 30 jun 2023Pódcast · 2 vocesDouwe Kiela on Data, Retrieval and Enterprise AIInvitado: Douwe Kiela · Presenta: Harry StebbingsThe Contextual AI CEO discusses language model trade-offs, evaluation, open models and the hurdles to enterprise use.
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No Priors: AI, Machine Learning, Tech, & Startups· 29 jun 2023Pódcast · 2 vocesThree IPOs Later, Frank Slootman Still Thinks the Job Is UrgencyPresenta: Sarah Guo, Elad GilSnowflake's CEO tells No Priors how he picked the right elevator, turned a 15-person backup startup into an EMC acquisition, and why a data lake is a landfill you should not train on.
6:49ENMatthew Berman· 21 jun 2023Reddit’s API Changes, AI Training Data and the Open InternetMatthew Berman · Forward FutureMatthew Berman argues that the 2023 Reddit API dispute exposed tensions between AI data demand, third-party developers and the people who create online content.
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Lex Fridman· 18 jun 2023Pódcast · 2 vocesWikipedia Worked Once Writing Stopped Feeling Like Grad SchoolInvitado: Jimmy Wales · Presenta: Lex FridmanJimmy Wales tells Lex Fridman how Nupedia's seven-stage review died, why Wikipedia still refuses ads and governments, and what large language models should actually do with an encyclopedia.
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Cognitive Revolution "How AI Changes Everything"· 16 jun 2023PódcastFrom $500,000 to $50,000: MosaicML Made Training Your Own Model a Priced ProductPresenta: Nathan LabenzJonathan Frankle and Abhi Venigalla explain who is training custom LLMs, why extraction beats chat, and how ALiBi stretches a 65k context window.
2:00:19ENCognitive Revolution "How AI Changes Everything"· 6 jun 2023Pódcast1.5 Million GPT-4 Fairy Tales Let a 33-Million-Parameter Model Out-Reason GPT-2Presenta: Nathan LabenzTry this fill-in: Lily likes cats and dogs. She asked her mom for a dog. Mom said no, so she asked for a…
10:16ENMatthew Berman· 21 may 2023DarkBERT: Adapting a Language Model to Dark-Web TextMatthew Berman · Forward FutureMatthew Berman reviews research on a RoBERTa-based model and its cybersecurity evaluations.
1:13:52ENMatthew Berman· 15 abr 2023Andriy Mulyar on GPT4All, Data Quality and Open Local ModelsMatthew Berman, Andriy Mulyar · Forward FutureThe Nomic AI co-founder explains how GPT4All emerged, why training data matters, and the tradeoffs between local and centralized AI.
8:02ENMatthew Berman· 12 abr 2023Meta’s Segment Anything: Promptable Image Masks and the SA-1B DatasetMatthew Berman · Forward FutureIn April 2023, Matthew Berman reviews Meta’s Segment Anything project and demonstrates selecting image regions with clicks, boxes and automatic mask generation. The model segments pixels; it does not by itself name every object or guarantee accurate results on every image.
6:24ENMatthew Berman· 6 abr 2023BloombergGPT: Mixing Financial and General Data for a Language ModelMatthew Berman · Forward FutureMatthew Berman examines the 2023 finance-focused research model, its training corpus, evaluation and decision not to release weights.
5:08ENMatthew Berman· 3 abr 2023Chatting with a PDF in Colab Using LangChain and a Vector IndexMatthew Berman · Forward FutureMatthew Berman demonstrates a 2023 PDF question-answering notebook; its retrieval workflow does not fine-tune model weights and its revenue example is incorrect.
1:29:31ENCognitive Revolution "How AI Changes Everything"· 30 mar 2023Pódcast130,000 Teleop Demos: Google's GPT Playbook for RobotsPresenta: Nathan LabenzKeerthana Gopalakrishnan of Google Robotics tells Nathan Labenz how RT-1, SayCan, and PaLM-E turn language-model scaling into kitchen-ready mobile manipulators.
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跟李沐学AI· 12 ene 2023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。
2:31:48ENLex Fridman· 28 dic 2021Pódcast · 2 vocesA Car That Cannot Drive Itself Will Be About as Useful as a HorseInvitado: Elon Musk · Presenta: Lex FridmanIn a Lex Fridman conversation built around Tesla Autopilot, Elon Musk argues that every driver input is an error, that today’s hardware is already enough for full self-driving, and that watching the human will soon matter less than making the system safer than a person.
1:28:46ENLex Fridman· 4 ene 2021Pódcast · 2 vocesThe Speech Company That Gets Paid to Label Its Own Training DataInvitado: Dan Kokotov · Presenta: Lex FridmanRev VP of engineering Dan Kokotov tells Lex Fridman why a $1.25-a-minute human transcript, a 14% machine word-error rate, and a two-sided freelancer market are the same flywheel.
1:12:03ENLex Fridman· 5 may 2020Pódcast · 2 vocesMice Don't Get Alzheimer's: Daphne Koller on Disease in a DishInvitado: Daphne Koller · Presenta: Lex FridmanThe Coursera co-founder and insitro CEO on why most diseases are not one disease, how to turn cells into data, and why overconfident neural nets can kill.
1:17:29ENLex Fridman· 23 sept 2019Pódcast · 2 vocesThe Algorithm Is Already Better. The Clinic Still Uses 1967.Invitado: Regina Barzilay · Presenta: Lex FridmanMIT's Regina Barzilay on why deep learning already beats the breast-cancer 'density' score — and why data, liability, and incentives still will not move.
57:44ENLex Fridman· 1 ago 2019Pódcast · 2 vocesKevin Scott: Treat AI Like a Hash Table, and Measure Platforms by What Others EarnInvitado: Kevin Scott · Presenta: Lex FridmanMicrosoft's CTO talks radical markets, data dignity, Dunbar's number, and why a platform fails if only a handful of companies decide what AI is for.
32:45ENLex Fridman· 12 abr 2019Pódcast · 2 vocesElon Musk: Every Driver Input Is an Error Tesla Autopilot Must EliminateInvitado: Elon Musk · Presenta: Lex FridmanAfter MIT published a study of functional vigilance on Autopilot, Lex Fridman sat down with Musk to argue about cameras on drivers, fleet data, and whether humans still belong in the loop.
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Lenny's PodcastPódcast · 2 vocesLook Outside the Building: Shaun Clowes on Why Most PMs Fall Short and How AI Changes the JobInvitado: Shaun Clowes · Presenta: Lenny RachitskyConfluent's chief product officer explains how to become a far better product manager, why data matters more than models, and what AI will and won't do to SaaS.
1:03:59ENCognitive Revolution "How AI Changes Everything"PódcastBuilding a World Model of Life: Biohub's Alex Rives on Why Better Measurement Must Come Before Virtual CellsPresenta: Nathan LabenzBiohub's head of science explains why today's virtual cell models fall short, how a $1.8 billion data push aims to fix it, and what a five-year information-level model of the cell could unlock.
1:07:08ENLenny's PodcastPódcast · 2 vocesIf the Model Is the Product, the Eval Is the PRD: Inside Mercor's RiseInvitado: Brendan Foody · Presenta: Lenny RachitskyMercor CEO Brendan Foody explains why AI labs will pay almost anything for expert-written evals, how his company grew from $1 million to a $400 million run rate in 16 months, and what that means for jobs and founders.
1:10:32ENLenny's PodcastPódcast · 2 vocesA Billion Dollars, No VC, Under 100 People: Surge AI's Edwin Chen on Data Quality and Where AI Is HeadingInvitado: Edwin Chen · Presenta: Lenny RachitskySurge AI's founder explains how a bootstrapped team built the leading human-data company, why he distrusts benchmarks, and how reinforcement learning environments are the next frontier.Cargar másMostrando 24 de 96