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361 件
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1:20:44EN
Cognitive Revolution "How AI Changes Everything"· 2024年3月30日ポッドキャストSeeing Like a Mamba: Vision, Rotting States, and a Cell Model in 90 Daysホスト Nathan LabenzNathan Labenz and Jason Meaux survey the vision papers, long-context experiments, and biology work that followed the original Mamba release.モデルと学習AI researchTransformers & attention+3
スライド 5 枚22:17EN
Matthew Berman· 2024年3月21日Q* Rumors, Energy-Based Models, and Research on ReasoningMatthew Berman, Yann Lecun · Forward FutureMatthew Berman examines an anonymous, unverified account of Q* and compares its ideas with published research on teaching language models to reason.Reasoning & test-time computeモデルと学習AI research+2
スライド 3 枚8:26EN
Matthew Berman· 2024年3月18日Testing Grok on X After the 2024 Grok-1 Weight ReleaseMatthew Berman · Forward FutureMatthew Berman tries coding and reasoning prompts in the hosted Grok interface, with mixed results.Open-weight modelsBenchmarksモデルと学習+1
スライド 2 枚4:49EN
Matthew Berman· 2024年3月17日xAI Releases Grok-1 Base Weights Under Apache 2.0Matthew Berman · Forward FutureMatthew Berman discusses the March 2024 release of a 314-billion-parameter mixture-of-experts model and the context of Elon Musk’s dispute with OpenAI.Foundation ModelsOpen-weight modelsモデルと学習+1
スライド 4 枚19:59EN
Matthew Berman· 2024年3月12日Testing Model Responses to Masked Harmful RequestsMatthew Berman · Forward FutureMatthew Berman compares refusals, decoding errors and inconsistent responses in informal 2024 experiments across several language models.AI SafetyAgent red teamingセキュリティと安全性+1
2:47:17EN
Lex Fridman· 2024年3月7日ポッドキャスト · 2 人If You Want Human-Level AI, Abandon Generative Modelsゲスト Yann Lecun · ホスト Lex FridmanYann LeCun tells Lex Fridman why autoregressive LLMs cannot plan, remember, or understand the physical world — and why open source is the only democratic answer.モデルと学習World modelsAGI(汎用人工知能)+3
スライド 5 枚13:57EN
Matthew Berman· 2024年2月27日Mistral Large: A 2024 Review of Coding, Reasoning and Safety ResponsesMatthew Berman · Forward FutureMatthew Berman reviews Mistral’s launch claims and tests the model with a small set of prompts.モデルと学習BenchmarksAI Safety+1
スライド 3 枚23:00EN
Matthew Berman· 2024年2月22日Testing Google Gemma 7B at Launch: Setup MattersMatthew Berman · Forward FutureMatthew Berman compares local and hosted tests of Google’s early open-weight model.Open-weight models評価(Evals)モデルと学習
1:58:43EN
Cognitive Revolution "How AI Changes Everything"· 2024年2月7日ポッドキャストA Worm With 302 Neurons Already Makes Trade-offs. AI Is Still on the Same Ladder.ホスト Nathan LabenzMax Bennett maps 600 million years of brain evolution onto five breakthroughs — and asks which rungs today's models have actually reached.モデルと学習AI HistoryNeuroscience & AI+3
スライド 2 枚0:42EN
Matthew Berman· 2024年1月31日LLaVA 1.6 Adds Higher-Resolution Image UnderstandingMatthew Berman · Forward FutureMatthew Berman reviews the January 2024 release of LLaVA 1.6 and its local availability through Ollama.Multimodal AIモデルと学習Local inference+1
40:58EN
No Priors: AI, Machine Learning, Tech, & Startups· 2024年1月25日ポッドキャスト · 2 人99% of Factory Robots Are Dumb. Covariant Wants the Smart Ones Working in Warehouses Firstホスト Sarah Guo, Elad GilFormer OpenAI researcher Peter Chen explains why robot foundation models have to be trained on production floors, not in labs.モデルと学習RoboticsFoundation Models+3
スライド35:28EN
Matthew Berman· 2024年1月23日Sam Altman on Future AI Models, Copyright and the Limits of DeploymentMatthew Berman, Ina Fried, Sam Altman · Forward FutureIn a January 2024 Davos interview, OpenAI’s CEO discusses model progress, election risks, military use and customization. Matthew Berman responds to the claims and their implications.OpenAIモデルと学習安全性とガバナンス+2
2:30:06EN
Cognitive Revolution "How AI Changes Everything"· 2023年12月22日ポッドキャストTrained on a Thirtieth of GPT-4's Tokens, Mamba Beat Transformers on Home Turfホスト Nathan LabenzIn a solo emergency episode, Nathan Labenz argues that Albert Gu and Tri Dao's selective state space model is the first architecture since 2017 that deserves to share the Transformer’s throne.モデルと学習Transformers & attentionAI research+3
スライド 5 枚14:04EN
Matthew Berman· 2023年12月15日Mistral Medium in 2023: API Pricing and Informal Model TestsMatthew Berman · Forward FutureMatthew Berman compares the original Mistral Medium prototype with Mixtral and GPT-4, then tests coding, writing and reasoning through the API.モデルと学習BenchmarksAI cost & performance+2
スライド 8 枚20:49EN
Matthew Berman· 2023年12月12日Mixtral 8x7B: Mixture-of-Experts Architecture, Setup and Early TestsMatthew Berman · Forward FutureMatthew Berman reviews Mistral AI’s December 2023 open-weight model, demonstrates a cloud setup and tests its coding and reasoning responses.モデルと学習Open-weight modelsInference+2
1:19:24EN
Cognitive Revolution "How AI Changes Everything"· 2023年11月17日ポッドキャストA Toy Paper Did Not Prove LLMs Cannot Generalize. The Discourse Still Ran With It.ホスト Nathan LabenzNathan Labenz and Erik Torenberg unpack a viral DeepMind result, a weekend reproduction, and a premature war over voluntary AI commitments.モデルと学習AI research機械学習の基礎+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
スライド 5 枚11:05EN
Matthew Berman· 2023年11月7日Testing Dolphin 2.2, a Mistral 7B Fine-TuneMatthew Berman · Forward FutureMatthew Berman tries a small open-weight model on coding, formatting and reasoning prompts, with mixed results.Open-weight modelsBenchmarksモデルと学習+1
41:58EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年11月2日ポッドキャスト · 2 人Reliability is the bottleneck. Autonomy is what would make AI feel alive.ホスト Sarah Guo, Elad GilIlya Sutskever talks with Sarah Guo and Elad Gil about AlexNet, OpenAI’s capped-profit bet, why smaller models mainly lose reliability, and the line he draws for digital life.モデルと学習AGI(汎用人工知能)Scaling Laws+3
1:19:52EN
Cognitive Revolution "How AI Changes Everything"· 2023年10月18日ポッドキャスト1,000 H100s Take 115 Days; 22,000 Take Fiveホスト Nathan LabenzNathan Labenz and Trey Kollmer walk through cluster math that turns GPT-4-scale training into a weekly experiment, then four papers on search-augmented models, recursive code improvers, spatial maps inside Llama 2, and what networks do when they have no idea.モデルと学習AI researchModel Interpretability+3
スライド 5 枚13:11EN
Matthew Berman· 2023年10月5日Testing Mistral 7B OpenOrca: A 2023 Cloud Setup and Prompt TrialMatthew Berman · Forward FutureMatthew Berman runs a quantized OpenOrca variant on a rented GPU and reviews coding, writing and reasoning examples.Open-weight modelsLocal inferenceBenchmarks+2
37:01EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年9月28日ポッドキャスト · 2 人DNA Is Code, but You Compile It with a Pipetteホスト Sarah Guo, Elad GilGinkgo Bioworks CEO Jason Kelly tells No Priors why cells are worth the magic, why biology has no AWS, and why a pandemic should look like cybersecurity.モデルと学習AI for scienceBiosecurity+3
スライド 6 枚12:49EN
Matthew Berman· 2023年9月14日Falcon 180B: A 2023 Review of TII’s Open-Weight ModelMatthew Berman · Forward FutureMatthew Berman tests coding, reasoning and writing prompts while examining the model’s training scale and license.Open-weight modelsBenchmarksモデルと学習+1
スライド 4 枚4:35EN
Matthew Berman· 2023年9月5日Running WizardCoder on a Cloud GPU: A 2023 RunPod WalkthroughMatthew Berman · Forward FutureMatthew Berman demonstrates downloading a quantized 13B coding model into a hosted text-generation interface, then explains how to stop the pod and avoid ongoing charges.モデルと学習インフラとデプロイコーディングエージェント
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