[EN/CN SUB] Stanford CS224R Deep RL, CAG, AI Evals, Risk & Governance

NotebookLM review stream for AI course, workshop, event, and AI engineering summaries.

Main themes:

Stanford CS224R Deep Reinforcement Learning: RL foundations, behavior blueprints, imitation learning, behavior cloning, and generative imitation learning
CAG vs long context, retrieval, memory, and context engineering
AI evaluation, benchmark design, diagnostic frameworks, and broken evals
AI risk, autonomy failures, agent safety, OpenClaw, and secure agent deployment
AI governance, audit readiness, algorithmic accountability, and enterprise AI playbooks
MIT 6.S191, CS336, CME295, CME296, CS229, CS230, CS25, AIE/AIEEU, IBM Technology, reports, and recent AI explorations
Recent additions:

Stanford CS224R: Deep Reinforcement Learning Fundamentals and Foundations of Imitation Learning
CS224R media package: Beyond IID / RL problem formulation, Demystifying Deep RL, Imitation Learning Mechanics, and the architecture from behavior cloning to foundation-style imitation
Deep RL visual briefs: Deep RL Blueprints, DRL Logic Blueprint, Blueprint of Behavior, Generative Imitation Learning, Imitation Learning Architectures, and Mastering Imitation Learning
IBM Technology: CAG vs Long Context, AI risk, test-time compute, AI agent memory, multi-agent systems, and digital certificate management
AIE/AIEEU: The AI Sandbox, Velocity Shock, Any-to-Any multimodal agents, skill engineering, agent ownership, open benchmarking at scale, and evaluation workflows
CME296: From Noise to Masterpiece and Architecting Diffusion
Google I/O event summary, No Slop / Cline summary, NVIDIA sustainability, UCB NVIDIA supply-chain analysis, China OPS report, Humanoid 100 report
EN/IT and real-time Chinese/English subtitle experiments
CS336 L6-L17, CS25 Causal JEPA, CS229 LLM training/evaluation, and CS230 2025 L1-L3
Current focus:
Lectures, consulting, AI engineering education, and practical systems thinking:
https://learnbydoingwithsteven.github.io/

All tutorials, podcasts, and social links:
https://linktr.ee/learnbydoingwithsteven

Leave a comment with what you want to watch next. I will arrange more tutorials and sharing sessions in the coming months.

If you are an AI founder, engineer, researcher, or tech professional, Steven Data Talk is open for thoughtful conversations, hot takes, and field notes from real work.

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