Introduces CSS Dedup, a tool to automate UDJO optimization for faster, cleaner style sheets.
How to speed up binary search 6× by optimizing for CPU hardware, using mechanical sympathy techniques like branch prediction and SIMD.
A tribute to Dimitri Bertsekas, a pioneer in optimization and reinforcement learning, reflecting on his contributions and legacy.
An essay comparing optimization culture to elimination diets and GLP-1 drugs, critiquing the technical language of maxxing.
Analyzing an optimization solver for Airbus A380 seating arrangements to maximize airline revenue using Python and OR-Tools.
A monthly tech roundup for April 2026 covering GitHub outages, Vercel security holes, Copilot issues, Anthropic drama, and npm malware, plus music and link recommendations.
Explores how the metrics platforms expose (like engagement) shape developer behavior and product ethics, arguing they are not neutral technical choices.
Explores the theoretical links between optimization algorithms (like gradient descent) and control theory, analyzing them as dynamical systems.
Explores the minimum value of sums of cosines with integer frequencies, touching on the Chowla cosine conjecture and numerical exploration methods.
A lecture blog exploring surprising robustness and fragility in interconnected systems, drawing analogies between nonlinear control and optimization.
Explains the greedy rectangle merging algorithm for simplifying binary grids into non-overlapping rectangles, with a JavaScript implementation.
A professor reflects on the intersection of machine learning and control theory, discussing the Learning for Dynamics and Control (L4DC) conference and the need for a merged perspective.
A developer's enthusiastic recap of a specialized workshop on egraphs and compilers, covering technical discussions, potential collaborations, and project ideas.
A critical review of a research paper proposing Raft optimizations for faster reads/writes while preserving linearizability in distributed systems.
Explains the new Optimized Locking feature in SQL Server 2025, detailing how it reduces lock memory and improves concurrency.
Explores the tension between optimization and systems-level thinking in AI-driven scientific discovery and computational ethics.
A lecture reflection on the gap between mathematical theory and practical engineering in machine learning, arguing for social analysis over functional analysis.
A simplified, non-technical definition of reinforcement learning as an iterative optimization process based on external feedback.
Explores the fundamental differences between animal intelligence and AI/LLM intelligence, focusing on their distinct evolutionary and optimization pressures.
Explores the commercial Apache Iceberg catalog ecosystem, focusing on REST Catalog standards, optimization strategies, and architectural trade-offs.
