本文へスキップ

最新のポッドキャスト 知識。

Podwise が処理した新着エピソード。検索、閲覧し、アプリで続きを読めます。

要約したばかり

再生する前に、各エピソードの内容を読めます。

Stanford Online

Stanford CS329A Self-Improving AI Agents | Part 9 | Future Research Areas

AI 要約 Self-improving agents utilize test-time and train-time scaling, driven by verifiers and reinforcement learning to enhance reasoning in domains like math and coding. Achieving generalization requires diverse reasoning chains, often generated by multi-agent systems or iterative…

  • LLMs (Large Language Models)
  • Test-time Scaling
  • Train-time Scaling

English要約 · 文字起こし

Easy German: Learn German with native speakers | Deutsch lernen mit Muttersprachlern

710: Warum lebt Manuel so ordentlich?

AI 要約 Die persönliche Organisation und das Streben nach Ordnung stehen im Mittelpunkt, wobei die Diskussion die neurobiologischen Grundlagen von ADHS und das Konzept der Neurodiversität beleuchtet. Während feste Systeme für manche Menschen eine notwendige Stütze im Alltag darstellen,…

  • DSGVO
  • Truth Social
  • ADHS

30:59German要約 · 文字起こし

Stanford Online

Stanford CS329A Self-Improving AI Agents | Part 8 | Agentic Evaluations and Long Horizon Tasks

AI 要約 Agentic evaluations measure the progress of AI models in completing long-horizon, economically valuable tasks. The METR benchmark tracks a seven-month doubling trend in task duration capabilities, yet highlights that high-reliability success remains elusive. Complementing this,…

  • Agentic evaluations
  • SweeBench
  • GDPval

English要約 · 文字起こし

Stanford Online

Stanford CS329A Self-Improving AI Agents | Part 7 | Self-Improvement and Deep Research Agents

AI 要約 Improving large language model performance relies on leveraging search within the model's output space to curate high-quality solutions. AlphaCode demonstrated that massive-scale sampling, combined with filtering and clustering, allows models to solve complex competitive…

  • AlphaCode / AlphaCode 2
  • HumanEval
  • Gemini Pro

English要約 · 文字起こし

The Audit Podcast

IA on AI - Fall 2026 Audit Analytics & AI Conference: Key Takeaways

AI 要約 The fall 2026 Audit Analytics & AI Conference emphasized practical, production-ready AI applications for internal audit departments. Effective strategies include persona-based reporting, where AI agents tailor communication styles to specific stakeholder preferences, and…

  • Benford's Law
  • Persona-based reporting
  • Shadow IT

19:15English要約 · 文字起こし

Stanford Online

Stanford CS329A Self-Improving AI Agents | Part 6 | Train Time Scaling/Scaling RL

AI 要約 Train time scaling enhances AI reasoning capabilities by allowing models to learn from their own outputs, effectively substituting compute for parameter count. This approach leverages verification-rich domains like mathematics and coding to create closed-loop feedback systems.…

  • Train Time Scaling
  • Test Time Scaling
  • AIME (American Invitational Mathematics Examination)

English要約 · 文字起こし

さらに新しいエピソード

  1. 要約21 min
  2. 要約23 min
  3. 要約21 min
  4. Max Hodak: Average Is Not Good Enough

    Y Combinator

    要約57 min
  5. 要約18 min
  6. 要約
  7. 要約19 min
  8. Claude Code for normal people: skills, voice mode, and how to collaborate with AI

    How I AI (private feed for hi.fangyuhan@icloud.com)

    要約43 min
  9. 要約2 h 31 min
  10. The Bloomberg Terminal for AI Compute

    The Data Exchange with Ben Lorica

    要約45 min
  11. The AI Agent Platform for Everyone

    The AI Daily Brief: Artificial Intelligence News and Analysis

    要約00:28:23
  12. Ad Fraud Expert on Scams, Bots, Spoofs

    Ecommerce Conversations

    要約32 min
  13. 651: How YouTube Is Quietly Becoming An E-Commerce Platform

    The My Wife Quit Her Job Podcast With Steve Chou

    要約38:51
  14. 要約51:29
  15. 要約00:44:06
  16. 要約36 min
  17. 要約00:23:00
  18. Jack Abraham of Atomic: Incubators & Startup Studios

    Summation with Auren Hoffman

    要約50 min
  19. Episode 43 - Novation vs Consultant Switch

    Part3 With Me

    要約19 min
  20. Episode 36 - Contract Administration

    Part3 With Me

    要約41 min
  21. 要約00:33:49
  22. 要約23 min
  23. 要約22 min
  24. 要約27 min
  25. 要約15 min
Podwise

すべての新着に 要約を。

Podwise で番組をフォローし、聴く前に各新着エピソードを読みましょう。