最近更新されたチャンネル

選ぶとそのチャンネルだけを表示すべてのチャンネル →

絞り込み結果

51 件
並び順
1:34:11EN
Cognitive Revolution "How AI Changes Everything"· 2024年4月17日ポッドキャストFrom forty hours in a scanner to one: reconstructing what you see from a shared brain spaceホスト Nathan LabenzPaul Scotti explains how MindEye2 maps a new person's fMRI into CLIP with an hour of data, and why a linear layer plus better image generators changed the cost of reading minds.マルチモーダルとメディアBrain-Computer InterfacesNeuroscience & AI+3
1:27:01EN
Cognitive Revolution "How AI Changes Everything"· 2024年4月8日ポッドキャストThree Million Emails, Ten LLM Calls, Six Models: Shortwave's RAG Playbookホスト Nathan LabenzFirebase founder Andrew Lee walks Nathan Labenz through the retrieval stack that turned a Gmail inbox into a working AI assistant.RAG とナレッジ検索拡張生成(RAG)Vector search+3
1:43:54EN
Cognitive Revolution "How AI Changes Everything"· 2024年3月27日ポッドキャストFifteen Examples Can Poison GPT-4: Today's AI Systems Are Exploitable by Defaultホスト Nathan LabenzFAR AI founder Adam Gleave walks through cheap jailbreaks in GPT-4's APIs and amateur-level wins against superhuman Go engines, and why robustness is not arriving on its own.セキュリティと安全性AI security安全性とガバナンス+3
31:28EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年2月22日ポッドキャスト · 2 人Bolt Memory onto GPT-4 and Cut Hallucinations by up to 50%ホスト Sarah Guo, Elad GilPinecone CEO Edo Liberty tells Sarah Guo and Elad Gil how RAG, serverless vectors, and keeping knowledge outside the model make LLMs more reliable.RAG とナレッジ検索拡張生成(RAG)Vector search+3
1:06:39EN
Unsupervised Learning: With Jacob Effron· 2024年1月9日ポッドキャストOpenAI's First DevRel Writes 90% of His Code with ChatGPT — and Says Web Agents Still Need Yearsホスト Jacob EffronLogan Kilpatrick on picking GPT-3.5 versus GPT-4, why plugins stalled, and why the public internet is not ready for autonomous agents.企業と戦略AI StrategyPrompting & in-context learning+3
1:22:43EN
Cognitive Revolution "How AI Changes Everything"· 2024年1月9日ポッドキャストFive billion minutes of calls: why Dialpad trained its own business LLMホスト Nathan LabenzDan O’Connell on real-time speech, verticalizing the stack, and why he and Nathan Labenz disagree about when AI employees show up.企業と戦略音声 AIエンタープライズ AI+3
1:21:50EN
Cognitive Revolution "How AI Changes Everything"· 2023年11月14日ポッドキャストA 16K Context Window Holds About 350 Rows. That's Why Tables Need an Agent.ホスト Nathan LabenzGretel AI founder Alex Watson tells Nathan Labenz why most company data is still a spreadsheet, why GPT-4 is the wrong tool for generating it, and how differential privacy lets a model learn a disease without learning a patient.モデルと学習Synthetic dataData quality & curation+3
1:14:48EN
Cognitive Revolution "How AI Changes Everything"· 2023年11月8日ポッドキャストDevDay Probably Created Thousands of Startups, Says OpenAI's Logan Kilpatrickホスト Nathan LabenzThe day after OpenAI's first developer conference, Dev Relations lead Logan Kilpatrick tells Nathan Labenz why thin wrappers were never companies, why agents were deliberately not shipped fully autonomous, and what $2 million custom models are for.企業と戦略Product Strategyエージェント工学+3
1:32:40EN
Cognitive Revolution "How AI Changes Everything"· 2023年10月31日ポッドキャストThe Historian Who Taught GPT-3.5 to Beat GPT-4ホスト Nathan LabenzMark Humphries on a kilometer of unread paper, fur-trade jargon that embeddings cannot see, and why cheap processing will force history to be rewritten.RAG とナレッジ検索拡張生成(RAG)ファインチューニング+3
1:17:09EN
Cognitive Revolution "How AI Changes Everything"· 2023年9月26日ポッドキャストGPT-4 as Teacher, GPT-3.5 as Student: A Nine-Tenths Cost Cut and an AI Bundle Nobody Will Startホスト Nathan LabenzNathan Labenz reports that chain-of-thought traces from GPT-4 train a cheaper, faster 3.5, then argues for flooring the app accelerator, tapping the brake on GPT-5, and bundling a hundred AI tools for a hundred dollars.企業と戦略ファインチューニングSynthetic data+3
2:32:49EN
Cognitive Revolution "How AI Changes Everything"· 2023年9月12日ポッドキャストGPT-4 Failed a Hollow Top Hat. Hollywood's AI Deal Closed Only Half the Loopholes.ホスト Nathan LabenzWriter Trey Kollmer returns with a strike update, a copyright briefing, and a riddle that still fools the best model.企業と戦略AI researchファインチューニング+3
55:08EN
Cognitive Revolution "How AI Changes Everything"· 2023年8月29日ポッドキャストOne Model Inside 38 Products: Paige Bailey on How Google Trains and Ships PaLM 2ホスト Nathan LabenzAt Google I/O in May 2023, PaLM 2 arrived already running in more than two dozen products — and its lead product manager walks through what that actually took.モデルと学習Multimodal AI評価(Evals)+3
スライド 2 枚6:28EN
MBMatthew Berman· 2023年8月29日A Historical GPT-3.5 Fine-Tuning WalkthroughMatthew Berman · Forward FutureMatthew Berman demonstrates generating synthetic examples in Colab and training a model to use a distinctive tone.ファインチューニングSynthetic dataモデルと学習
52:48EN
Cognitive Revolution "How AI Changes Everything"· 2023年8月25日ポッドキャストOpenAI Cut Fine-Tuning 90 Percent, and Founders Crossed Llama 2 Off the Listホスト Nathan LabenzNathan Labenz and Erik Torenberg walk through GPT-3.5 Turbo fine-tuning, why self-hosting still loses on total cost, and what is actually working in code, school, and medicine.モデルと学習ファインチューニングAI cost & performance+3
1:40:44EN
Cognitive Revolution "How AI Changes Everything"· 2023年7月19日ポッドキャストGive the Model Time, Memory, and Tools: Nathan Labenz’s 2023 Field Guide to Using GPT-4ホスト Nathan LabenzPart two of the AI Scouting Report walks from H100 clusters and RLHF through chain-of-thought, retrieval, agents, and mixture-of-experts.エージェント検索拡張生成(RAG)Prompting & in-context learning+3
59:28EN
Cognitive Revolution "How AI Changes Everything"· 2023年6月16日ポッドキャストFrom $500,000 to $50,000: MosaicML Made Training Your Own Model a Priced Productホスト Nathan LabenzJonathan Frankle and Abhi Venigalla explain who is training custom LLMs, why extraction beats chat, and how ALiBi stretches a 65k context window.モデルと学習ファインチューニングPretraining & midtraining+3
スライド 4 枚11:42EN
MBMatthew Berman· 2023年5月31日Guanaco and QLoRA: A 2023 Fine-Tuning and Model TestMatthew Berman · Forward FutureMatthew Berman reviews the QLoRA paper, explains the reported memory savings and tries Guanaco 65B on an informal prompt set.ファインチューニングQuantizationOpen-weight models+1
1:25:35EN
Cognitive Revolution "How AI Changes Everything"· 2023年5月21日ポッドキャストTwo and a Half Years From 33.3% to 86.5%: Google Sent Foundation Models to Medical Schoolホスト Nathan LabenzVivek Natarajan walks Nathan Labenz through Med-PaLM and Med-PaLM 2: the data-light techniques, the nine-axis clinician evals, and why a high USMLE-style score is the wrong trophy.モデルと学習AI in healthcareファインチューニング+3
42:18EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年5月18日ポッドキャスト · 2 人Ten Percent of Search Is Health — and the Doctor Is Googling Tooホスト Sarah Guo, Elad GilGoogle researcher Karan Singhal on Med-PaLM 2, the real bar for medical language models, and why medicine is a harder alignment lab than chatbots.モデルと学習AI in healthcare安全性とガバナンス+3
37:18EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年5月4日ポッドキャスト · 2 人Use Retrieval for a Wi-Fi Password. Use Experts for a Company's Private Language.ホスト Sarah Guo, Elad GilGoogle Brain's Kelvin Guu on REALM, FLAN, model surgery, and why personalizing large models is still an unsolved interface problem.RAG とナレッジ検索拡張生成(RAG)ファインチューニング+3
1:21:06EN
Cognitive Revolution "How AI Changes Everything"· 2023年4月27日ポッドキャストEveryone Talks About RLHF. Almost Nobody Is Doing It.ホスト Nathan LabenzHumanloop CEO Raza Habib on why an LLM API is maybe five percent of a working product, and what actually fills the rest.プロダクトと UX評価(Evals)オブザーバビリティと信頼性+3
40:25EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年4月6日ポッドキャスト · 2 人A 6-Billion-Parameter Clone of ChatGPT’s Core Trickホスト Sarah Guo, Elad GilDatabricks CTO Matei Zaharia tells Sarah Guo and Elad Gil how Dolly learned instruction-following on fifty times less data than GPT-3 — and why he would rather look facts up than bake them into a trillion-parameter network.モデルと学習Open-weight modelsファインチューニング+3
1:56:16EN
Cognitive Revolution "How AI Changes Everything"· 2023年4月6日ポッドキャストThey Used Humans as Stand-In AIs. Now 250,000 People Run Elicit.ホスト Nathan LabenzOught's founders tell Nathan Labenz why open-ended reasoning has to be decomposed, supervised, and grounded—not scaled until it merely looks persuasive.RAG とナレッジエージェント工学評価(Evals)+3
1:22:36EN
Lenny's Podcastポッドキャスト · 2 人Stop Chasing AI News: Chip Huyen on What Actually Makes AI Products Betterゲスト Chip Huyen · ホスト Lenny RachitskyAuthor of AI Engineering walks through pre-training, post-training, RL, evals and RAG, then explains what separates companies that get value from AI from those that stall.プロダクトと UXファインチューニング検索拡張生成(RAG)+3
もっと見る51 件中 24 件を表示