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Stanford Online3 août

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

Résumé IA 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

EnglishRésumé · Transcription

Easy German: Learn German with native speakers | Deutsch lernen mit Muttersprachlern14 nov.

710: Warum lebt Manuel so ordentlich?

Résumé IA 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

30:59GermanRésumé · Transcription

Stanford Online3 août

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

Résumé IA 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

EnglishRésumé · Transcription

Stanford Online3 août

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

Résumé IA 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

EnglishRésumé · Transcription

The Audit Podcast11 nov.

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

Résumé IA 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

19:15EnglishRésumé · Transcription

Stanford Online3 août

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

Résumé IA 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.…