Real World Recommendation System - Part 1

- Nikhil Garg tl;dr: "FAANG and other top tech companies have independently converged on a common architecture for production grade recommendation systems." This architecture is domain / vertical agnostic and can power all sorts of applications — from e-commerce and feeds to search, notifications, etc... Nikhil starts from the basics, explains nuances and describes this universal architecture.

featured in #310

Introducing Swift Async Algorithms

- Tony Parker tl;dr: Part of Swift’s move toward safe, simple, and performant asynchronous programming, Swift have launched a package of algorithms, which has 3 main goals: (1) Integration with async/await. (2) Provide a home for time-based algorithms. (3) Be cross-platform and open source.

featured in #305

Understanding Layout Algorithms

- Josh W Comeau tl;dr: "The key realization I had is that CSS is so much more than a collection of properties. It's a constellation of inter-connected layout algorithms. Each algorithm is a complex system with its own rules and secret mechanisms." Josh looks at how this new lens can help make sense of what's happening in CSS. And use that lens to "solve a surprisingly-common mystery."

featured in #304

Algorithms For Decision Making

- Mykel Kochenderfer Tim Wheeler Kyle Wray tl;dr: "This book provides a broad introduction to algorithms for decision making under uncertainty. We cover a wide variety of topics related to decision making, introducing the underlying mathematical problem formulations and the algorithms for solving them."

featured in #299

Algorithms For Modern Hardware

- Sergey Slotin tl;dr: "This is an upcoming high performance computing book. Its intended audience is everyone from performance engineers and practical algorithm researchers to undergraduate computer science students who have just finished an advanced algorithms course and want to learn more practical ways to speed up a program."

featured in #297

Self-Parking Car In 500 Lines Of Code

- Oleskii Trekhleb tl;dr: "Step-by-step we're going to break down a high-level task of creating the self-parking car to the straightforward low-level optimization problem of finding the optimal combination of 180 bits (finding the optimal car genome)."

featured in #257

Quadratic Algorithms Are Slow (And Hashmaps Are Fast)

- Julia Evans tl;dr: Julia guides us through what a quadratic time function looks like, why it's slow, how to convert a quadratic algorithm into a linear one using a hashmap.

featured in #252

Solving Martin Gardner's Chess Problem Using Simulated Annealing

- Dennis Yurichev tl;dr: The problem is the maximum-attack problem, placing 8 pieces (not the pawns) on squares to attack the largest number of squares and, the converse, the minimum-attack problem using the simulated annealing algorithm.

featured in #249

Reddit Interview Problems: The Game Of Life

- Alex Golec tl;dr: Alex runs through an interview question at Reddit: "Suppose you have an M by N board of cells, where each cell is marked as "alive" or "dead." This arrangement of the board is called the "state," and our task is to compute the cells in the next board state according to a set of rules:" He runs through the solutions in this post.

featured in #247

5000x Faster CRDTs: An Adventure in Optimization

tl;dr: The author read a paper about implementing collaborative editing tools and one of the algorithms mentioned took over 3 seconds to process, which is slow. It was his own algorithm, and in this post he makes amends and shows hot to speed the tools up.

featured in #242