Welcome to my blog! Here I share thoughts on AI research, machine learning, and technology trends.
📅 Published:
Every mature science has its central dogma. Biology has DNA → RNA → Protein. What is ours? Intelligence is the compression of experience into generalization. This essay explores how compression theory explains pre-training, post-training, and alignment — and why understanding compression losses may be the key frontier in AI.
📅 Published:
A practical guide to RL environments using Pokemon Red as a case study. Covers the agent-environment loop, observation and action spaces, reward design, trajectories, graders, and the credit assignment problem—with real code examples and lessons from training an LLM-based gameplay agent.
📅 Published:
A comprehensive guide to post-training techniques for large language models, covering supervised fine-tuning, RLHF, reward models, and practical implementation details. This guide walks through the entire journey from pre-training to instruct-tuned models with hands-on examples and best practices.
Published:
PyTorch tutorial that takes you from basic tensor operations to advanced topics like attention mechanisms and mixed precision training.