Zen and the Art of Machine Learning Research
Summary
This essay outlines a pragmatic approach to AI research, emphasizing the need to balance reading with hands-on building. It advocates focusing on fundamentals (e.g., cross-entropy, SVD, policy gradients), avoiding excessive benchmarking hype, and developing disciplined, skeptical experimentation. It also highlights the value of long-term, curiosity-driven work and practical workflows for rapid iteration.