The Infrastructure Round
Scaling, serving, and optimizing AI systems. Custom kernels, inference engines, and production infrastructure.
4 articles covering mlops & production
Why modern AI teams are handcrafting GPU kernels—from FlashAttention to TPU Pallas code—and how smarter tooling is making silicon-level tuning accessible.
How PagedAttention, Continuous Batching, Speculative Decoding, and Quantization unlock lightning-fast, reliable large language model serving.
A reader-friendly guide to scaling AI models beyond the data pipeline—from training loops and distributed frameworks to checkpoints, mixed precision, and fault tolerance.
A deep dive into how datasets and dataloaders power modern AI—from the quiet pipeline that feeds models to the sophisticated tools that make training efficient. Understanding the hidden engine that keeps AI systems running.