“Hunger makes me a modern girl”

I know Carrie Brownstein through “Portlandia,” a quirky sketch show she’s been doing with Fred Armisen for the last couple of years. I’m a huge fan of how accurately “Portlandia” pokes fun at alternative-culture so commonly associated with Pacific Northwest.1 What I learned later, only after doing some research on Fred and Carrie, is that they were both well-known before the show even started. Fred, to a perhaps lesser extent, through SNL, and Carrie, probably to a much greater extent, through Sleater-Kinney.

How are zlib, gzip and Zip related?

Abhishek Jain asks Stack Overflow about the differences between zlib, gzip and Zip, and gets a fascinating and very insightful response from none other than Mark Adler. I particularly like the comment Adler made when the OP asked about referenecs for his answer. I am the reference, having been part of all of that. This post could be cited in Wikipedia as an original source. This, to me, is a perfect example of the enormous impact of open source and free software libraries developed in the 80s and 90s have on modern-day computing.

Married

After many, many years of careful consideration, my lovely fiancee and I decided to get married. I’m posting this with a 1-month delay, because we were busy with climbing, working and traveling a lot. So far being married has been great, I recommend it to everyone. Photograph by Konrad Ciok

AlphaGo wins with Lee Sedol

Google Deep Mind’s AlphaGo won two games against the world go champion, Lee Sedol. This is a ginormous triumph of statistical methods in general and machine learning in particular over “symbolic AI.” I remember writing an essay for a class in philosophy some years ago about the progress of AI game engines and the somewhat unimpressive achievements of Deep Blue. It was of course exciting to see a computer beat a reigning chess world champion, but underneath all the heuristics IBM implemented for chess, it was all “brute force.

Apple's letter about the San Bernardino case

lazaroclapp: There are basically two groups of large software companies around right now: those which make their business by collecting data, and those which make their business by licensing software. The first group has an overwhelming incentive to not support privacy too strongly. The second group has an overwhelming incentive to not allow too much openness. Until a better business model (or zero-knowledge machine learning) is found, no large for profit company can support both goals to their final conclusion.