The Google Brain Residency — summary of outputs, with pointers to papers and GitHub repos, from the Google program that helps individuals from diverse educational backgrounds and experiences to dive into research in machine learning and deep learning.
Findings of The Shift Commission on Work, Workers, and Technology — their exploration of four scenarios. Rock-Paper-Scissors Economy: Less work, mostly tasks. Jump Rope Economy: More work, mostly tasks. King of the Castle Economy: Less work, mostly jobs. Go Economy: More work, mostly jobs. I like the two axis scenario framework: less/more work; jobs or tasks.
Learn faster. Dig deeper. See farther.
Join the O'Reilly online learning platform. Get a free trial today and find answers on the fly, or master something new and useful.
Spotlight Feedback Framework — depending on the questions your customers ask, you can categorize your problem as user experience (“how do I X?”, “what happens when X?”, “I tried to X”); product marketing (“can you/I X?”, “how do you compare to X?”, “how are you different than X?”, “why should I use you for X?”); and positioning (“I’m probably not your target customer…”, “I’m sure I’m wrong, but I thought…”). That distinction between “can I…” and “how do I…” is subtle; the former means you’ve not shared that your product can do the thing, while the latter means you’ve not made the method discoverable without explanation. (via Product Habits)
Verdi — Verdi is a framework from the University of Washington to implement and formally verify distributed systems. Verdi supports several different fault models, ranging from idealistic to realistic. Interesting on two fronts: proving system correctness may lead to useful tools and software development systems, and work on this to date has largely been around single-threaded programs. Anyone who has debugged multi-threaded code knows how much more difficult it is to reason about such systems.