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슬라이드 2장4:48EN
Matthew Berman· 2023년 7월 12일PoisonGPT: 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.AI securityData quality & curationModel Interpretability+1
54:00EN
20VC with Harry Stebbings· 2023년 6월 30일팟캐스트 · 2명Douwe Kiela on Data, Retrieval and Enterprise AI게스트 Douwe Kiela · 진행자 Harry StebbingsThe Contextual AI CEO discusses language model trade-offs, evaluation, open models and the hurdles to enterprise use.엔터프라이즈 AI검색 증강 생성(RAG)Data quality & curation+2
51:22EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023년 6월 29일팟캐스트 · 2명Three IPOs Later, Frank Slootman Still Thinks the Job Is Urgency진행자 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.기업과 전략Company BuildingLeadership+3
6:49EN
Matthew Berman· 2023년 6월 21일Reddit’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.Open-source ecosystemsData quality & curationPrivacy & data governance+2
3:15:07EN
Lex Fridman· 2023년 6월 18일팟캐스트 · 2명Wikipedia Worked Once Writing Stopped Feeling Like Grad School게스트 Jimmy Wales · 진행자 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.오픈소스와 커뮤니티Open-source ecosystemsFree Speech+3
59:28EN
Cognitive Revolution "How AI Changes Everything"· 2023년 6월 16일팟캐스트From $500,000 to $50,000: MosaicML Made Training Your Own Model a Priced Product진행자 Nathan LabenzJonathan Frankle and Abhi Venigalla explain who is training custom LLMs, why extraction beats chat, and how ALiBi stretches a 65k context window.모델과 학습파인튜닝Pretraining & midtraining+3
2:00:19EN
Cognitive Revolution "How AI Changes Everything"· 2023년 6월 6일팟캐스트1.5 Million GPT-4 Fairy Tales Let a 33-Million-Parameter Model Out-Reason GPT-2진행자 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…모델과 학습Synthetic dataData quality & curation+3
슬라이드 4장10:16EN
Matthew Berman· 2023년 5월 21일DarkBERT: Adapting a Language Model to Dark-Web TextMatthew Berman · Forward FutureMatthew Berman reviews research on a RoBERTa-based model and its cybersecurity evaluations.AI securityPretraining & midtrainingBenchmarks+1
1:13:52EN
Matthew Berman· 2023년 4월 15일Andriy 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.Local inferenceOpen-weight modelsData quality & curation+2
슬라이드 5장8:02EN
Matthew Berman· 2023년 4월 12일Meta’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.Computer Vision비전과 영상Deep Learning+1
슬라이드 5장6:24EN
Matthew Berman· 2023년 4월 6일BloombergGPT: 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.금융 AI모델과 학습평가(Evals)+1
슬라이드 3장5:08EN
Matthew Berman· 2023년 4월 3일Chatting 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.검색 증강 생성(RAG)Document understanding & OCR개발 워크플로와 테스트+1
1:29:31EN
Cognitive Revolution "How AI Changes Everything"· 2023년 3월 30일팟캐스트130,000 Teleop Demos: Google's GPT Playbook for Robots진행자 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.에이전트RoboticsMultimodal AI+3
슬라이드 8장1:03:29ZH
跟李沐学AI· 2023년 1월 12일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。Multimodal AI모델과 학습Data quality & curation
2:31:48EN
Lex Fridman· 2021년 12월 28일팟캐스트 · 2명A Car That Cannot Drive Itself Will Be About as Useful as a Horse게스트 Elon Musk · 진행자 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.보안과 안전Autonomous DrivingRobotics+3
1:28:46EN
Lex Fridman· 2021년 1월 4일팟캐스트 · 2명The Speech Company That Gets Paid to Label Its Own Training Data게스트 Dan Kokotov · 진행자 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.멀티모달과 미디어음성 AI사람 참여 검증(HITL)+3
1:12:03EN
Lex Fridman· 2020년 5월 5일팟캐스트 · 2명Mice Don't Get Alzheimer's: Daphne Koller on Disease in a Dish게스트 Daphne Koller · 진행자 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.AI in healthcareComputational BiologyAI for science+3
1:17:29EN
Lex Fridman· 2019년 9월 23일팟캐스트 · 2명The Algorithm Is Already Better. The Clinic Still Uses 1967.게스트 Regina Barzilay · 진행자 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.AI in healthcareAI for scienceData quality & curation+3
57:44EN
Lex Fridman· 2019년 8월 1일팟캐스트 · 2명Kevin Scott: Treat AI Like a Hash Table, and Measure Platforms by What Others Earn게스트 Kevin Scott · 진행자 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.기업과 전략AI StrategyProduct Strategy+3
32:45EN
Lex Fridman· 2019년 4월 12일팟캐스트 · 2명Elon Musk: Every Driver Input Is an Error Tesla Autopilot Must Eliminate게스트 Elon Musk · 진행자 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.보안과 안전Autonomous Driving사람 참여 검증(HITL)+3
1:21:35EN
Lenny's Podcast팟캐스트 · 2명Look Outside the Building: Shaun Clowes on Why Most PMs Fall Short and How AI Changes the Job게스트 Shaun Clowes · 진행자 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.제품과 UXProduct ManagementAI Product Management+3
1:03:59EN
Cognitive Revolution "How AI Changes Everything"팟캐스트Building a World Model of Life: Biohub's Alex Rives on Why Better Measurement Must Come Before Virtual Cells진행자 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.모델과 학습AI for scienceComputational Biology+3
1:07:08EN
Lenny's Podcast팟캐스트 · 2명If the Model Is the Product, the Eval Is the PRD: Inside Mercor's Rise게스트 Brendan Foody · 진행자 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.평가와 관측 가능성평가(Evals)Data quality & curation+3
1:10:32EN
Lenny's Podcast팟캐스트 · 2명A Billion Dollars, No VC, Under 100 People: Surge AI's Edwin Chen on Data Quality and Where AI Is Heading게스트 Edwin Chen · 진행자 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.모델과 학습Company BuildingData quality & curation+3
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