Reinforcement Learning — From Intuition to Algorithms
A narrative-first walkthrough of reinforcement learning, starting with everyday intuition and ending with the math behind Q-learning and DQN.
Posts
All the articles I've posted.
-
-
Tongue Twister Practice Sheet — Clarity and Fluency for Tech Talks
A structured articulation and pacing warm-up designed to help technologists speak with clarity and confidence in high-stakes meetings.
-
The Custom Kernel Craze — Why Developers Are Taking the Wheel on GPU Optimization
Why modern AI teams are handcrafting GPU kernels—from FlashAttention to TPU Pallas code—and how smarter tooling is making silicon-level tuning accessible.
-
When AI Sees and Speaks — The Rise of Vision-Language Models
UpdatedA high level view on how modern vision-language models connect pixels and prose, from CLIP and BLIP to Flamingo, MiniGPT-4, Kosmos, and Gemini.
-
vLLM and the Trilogy of Modern LLM Scaling
How PagedAttention, Continuous Batching, Speculative Decoding, and Quantization unlock lightning-fast, reliable large language model serving.
-
Diffusion — From Molecules to Machines
UpdatedA clear introduction to diffusion and guided diffusion — how a simple physical process became a foundation for modern generative AI, from Stable Diffusion to robotics and protein design.