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Good (Technical) Reads

Alex Kranias

This is mostly for myself as it's easier to manage than an obscure Obsidian doc I keep losing track of on my laptop. A list of blogs, textbooks, websites, lectures, etc. that I find and think are interesting / useful.

Machine Learning / Deep Learning

  1. An Alchemist's Guide to Deep Learning
  2. Reinforcement Learning from Human Feedback
  3. Foundations of Computer Vision
  4. An Introduction to Information Retrieval

Systems

  1. UIUC x NVIDIA Course
  2. How to Optimize a CUDA Matmul Kernel for cuBLAS-like Performance
  3. "Numbers Everyone Should Know" from Jeff Dean
  4. Collective Communication Primitives
  5. www.quant.exposed
  6. Scaling Memcache at Facebook (NSDI '13)
  7. Building Software Systems At Google and Lessons Learned
  8. Fast, lazy container loading in Modal.com
  9. https://neurips.cc/virtual/2025/loc/san-diego/talk/127740
  10. Designing Data-Intensive Applications
  11. Scaling HNSWs

Algorithms / Theory

  1. Streaming Algorithms
  2. Advanced Algorithms
  3. Information Theory, Inference, and Learning Algorithms - David J.C. MacKay

HCI

  1. Macintosh Human Interface Guidelines
  2. It's hard to justify Tahoe icons

Misc

  1. Everything I know about good API design
  2. Exploring Large HTML Documents in the Web
  3. Semantic Compression
  4. Challenging projects every programmer should try