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Stanford Online8月3日

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 Muttersprachlern11月14日

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 Online8月3日

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 Online8月3日

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 Podcast11月11日

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 Online8月3日

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.…