Responsible deployment of machine learning
Ben Lorica explains how to guard against flaws and failures in your machine learning deployments.
Ben Lorica explains how to guard against flaws and failures in your machine learning deployments.
Joshua Bloom explains why the real revolution will happen—in improved and saved lives—when machine learning automation is coupled with industrial data.
Bruno Fernandez-Ruiz discusses the tradeoffs we make to ensure safer transportation.
TouchID for SSH, Pen Testing Checklist, Generativity, and AI Data
Analog Computing, Program Synthesis, Midwestern Investment, and Speed Email
Campaign Cybersecurity, Generated Games, Copyright-Induced Style, and Tech Ethics
Creepy Kid Videos, Cache Smearing, Single-Image Learning, and Connected Gift Guide
Lessons learned from building engineering teams under pressure.
Object Models, Open Source Voice Recognition, IoT OS, and High-Speed Robot Wars
Scale changes the problems of privacy, security, and honesty in fundamental ways.
Avoiding State Surveillance, Parallel Algorithms, Smart Tactics, and Voting Security
Code for One, Grid Component, Tinder Data, and Engineering Reorg
PV Growth, Digital Rights, Unit Testing, and Open Source Innovation
Modern Spam, Communist Cybernetics, Computer Simulation, and Retail Big Data
Fuzzing, Time Series, Unix 1ed, and Failing
Decision-making, Code Duplication, Container Security, and Information vs Attention
Storytelling, Decompilation, Face Detection, and Dependency Alerts
Ancient Data, Tech Ethics, Session Replay, and Cache Filesystem