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スライド 3 枚6:50EN
Matthew Berman· 2023年3月19日Running LLaMA and Alpaca Locally: A 2023 Dalai TutorialMatthew Berman · Forward FutureMatthew Berman demonstrates an early local-model setup on a MacBook Air and explains the settings that control generation.Local inferenceモデルと学習ファインチューニング+1
スライド 4 枚8:19EN
Matthew Berman· 2023年2月15日Leonardo.Ai in 2023: Generating Images, Remixing Models and Editing a CanvasMatthew Berman · Forward FutureMatthew Berman walks through Leonardo.Ai’s early image-generation interface, from style models and settings to community remixes, custom training and the beta canvas. Features and pricing have changed since this February 2023 demonstration.Generative mediaPrompting & in-context learningプロダクトと UX+1
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
23:54EN
No Priors: AI, Machine Learning, Tech, & Startupsポッドキャスト · 2 人Beyond GPT-7: The Customization Toolkit, Meta's Open Source Bet and the Return of Consumer AIホスト Sarah Guo, Elad GilIn a host-only episode, the No Priors hosts map the six levers for 10x to 100x better AI, explain fine-tuning, RAG and AI feedback, and ask why consumer social is suddenly interesting again.モデルと学習ファインチューニング検索拡張生成(RAG)+3
46:48EN
Unsupervised Learning: With Jacob EffronポッドキャストSnowflake's AI Stack: Small Models, the Text-to-SQL Iceberg, and Why Governance Comes Firstホスト Jacob EffronSnowflake head of AI Baris Gekken explains how Arctic and Cortex were built, where enterprise AI actually works today, and why precision, governance and evaluation matter more than raw model capability.企業と戦略インフラとデプロイエンタープライズ AI+3
1:22:17EN
Cognitive Revolution "How AI Changes Everything"ポッドキャストOne Set of Weights, Fourteen Medical Tasks: Inside Google's Multimodal Med-PaLM Mホスト 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.モデルと学習AI in healthcareMultimodal AI+3