Reinforcement Learning Course
Bellman Equations and Dynamic Programming
RL Part 3: Bellman expectation and optimality equations, policy iteration, value iteration, and why dynamic programming needs a model.
Archive
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Reinforcement Learning Course
Markov Decision Processes and Value Functions
RL Part 2: Markov decision processes, returns, policies, and value functions.
Reinforcement Learning
How to Beat GRPO Without Touching Model Weights
Berkeley beat GRPO by 10 points with 35× fewer rollouts and no GPU training,
Reinforcement Learning
How Top AI Labs Are Building RL Agents in 2026
The era of not writing custom reward functions.
Reinforcement Learning Course
Foundations of Reinforcement Learning
RL Part 1: Agents, environments, rewards, and why RL is different from supervised learning.
Claude
How We Cut Our Claude Code Token Usage 2.8x!
...using Karpathy's context engineering principles!
Classical ML and Deep Learning
Diffusion LLMs from the Ground Up: Training, Inference, and Practical Engineering
Diffusion LLMs Part 2: How dLLMs scale to 100B parameters, the inference stack that makes them fast, hands-on code, and when to actually use them.
LLMOps
72 Techniques to Optimize LLMs in Production
...explained with usage.
