Nat has chaired the O'Reilly Open Source Convention and other O'Reilly conferences for over a decade. He ran the first web server in New Zealand, co-wrote the best-selling Perl Cookbook, and was one of the founding Radar bloggers. He lives in New Zealand and consults in the Asia-Pacific region.
The O-Ring Theory of DevOps (Adrian Colyer) — Small differences in quality (i.e, in how quickly and accurately you perform each stage of your DevOps pipeline) quickly compound to make very large differences between the performance of the best-in-class and the rest.
TensorFlow — Google released, as open source, their distributed machine learning system. The DataFlow programming framework is sweet, and the documentation is gorgeous. AMAZINGLY high-quality, sets the bar for any project. This may be 2015’s most important software release.
TensorFlow White Paper (PDF) — Compared to DistBelief [G’s first scalable distributed inference and training system], TensorFlow’s programming model is more flexible, its performance is significantly better, and it supports training and using a broader range of models on a wider variety of heterogeneous hardware platforms.
Neural Networks With Few Multiplications — paper with a method to eliminate most of the time-consuming floating point multiplications needed to update the intermediate virtual neurons as they learn. Speed has been one of the bugbears of deep neural networks.
Cybersecurity as RealPolitik — Dan Geer’s excellent talk from 2014 BlackHat. When younger people ask my advice on what they should do or study to make a career in cyber security, I can only advise specialization. Those of us who were in the game early enough and who have managed to retain an over-arching generalist knowledge can’t be replaced very easily because while absorbing most new information most of the time may have been possible when we began practice, no person starting from scratch can do that now. Serial specialization is now all that can be done in any practical way. Just looking at the Black Hat program will confirm that being really good at any one of the many topics presented here all but requires shutting out the demands of being good at any others.
Low-Power Deep Learning — it’s a media release for proprietary tech, but interesting that people are working on low-power deep learning neural nets. As Pete Warden noted, this kind of research will be at the center of smart sensors. (via Pete Warden)
Tesla’s Self-Improving Autopilot — it learns when you “rescue” (aka take control back from autopilot), so it’s getting better day by day. Musk said that Model S owners could add ~1 million miles of new data every day, which is helping the company create “high-precision maps.” Navteq, Google Maps, Waze … new map data is still valuable.
The Digital Revolution in Higher Education Has Already Happened (Clay Shirky) — and no-one noticed. I read half of this before going “holy crap this is good, who wrote it?” I’m a Shirky junkie (I bet his laundry lists cite Habermas and the Peace of Westphalia). At the current rate of growth, half the country’s undergraduates will have at least one online class on their transcripts by the end of the decade. This is the new normal. But, As long as we discuss online education as a pedagogic revolution rather than an organizational one, we aren’t even having the right kind of conversation. The dramatic adoption of online education is not mainly a change in the content of classes. It’s a change in the institutional form of college, a demand for more flexibility by students who have to manage the increasingly complicated triangle of work, family, and school.
System Automatically Converts 2-D to 3-D (MIT) — hilarious strategy! They constrained their domain: broadcast soccer games. The MIT and QCRI researchers essentially ran this process in reverse. They set the very realistic Microsoft soccer game “FIFA13” to play over and over again, and used Microsoft’s video-game analysis tool PIX to continuously store screen shots of the action. For each screen shot, they also extracted the corresponding 3-D map. […] For every frame of 2-D video of an actual soccer game, the system looks for the 10 or so screen shots in the database that best correspond to it. Then it decomposes all those images, looking for the best matches between smaller regions of the video feed and smaller regions of the screen shots. Once it’s found those matches, it superimposes the depth information from the screen shots on the corresponding sections of the video feed. Finally, it stitches the pieces back together. Brute-forcing soccer. Ok, perhaps “hilarious” for a certain type of person. I am that person.
Security and the Linux Kernel (WaPo) — the question is not “can the WaPo write intelligently about the Linux kernel and security?” (answer, by the way, is “yes”) but rather “why is the WaPo writing about Linux kernel and security?” Ladies and gentlemen, start your conspiracy engines.
TPP Might Prevent Governments from Auditing Source Code (Wired) — Article 14.17 of proposal, published at last today after years of secret negotiations, says: “No Party shall require the transfer of, or access to, source code of software owned by a person of another Party, as a condition for the import, distribution, sale or use of such software, or of products containing such software, in its territory.” The proposal includes an exception for critical infrastructure, but it’s not clear whether software involved in life or death situations, such as cars, airplanes, or medical devices would be included. One of many “what the heck does this mean for us?” analyses coming out. I’m waiting a few days until the analyses shake out before I get anything in a tangle.
Taiga — open source agile software project management tool (backlog, kanban, tasks, sprints, burndown charts, that sort of thing). (via Jef Vratny)
Confidant — a secret management system, for AWS, from Lyft. If you build services that need to talk to each other, it quickly gets difficult to distribute and manage permissions to those services. So, naturally, the solution is to add another service. (In accordance with the Fundamental Theorem of Computer Science.)
Gmail Suggesting Replies — In developing Smart Reply, we adhered to the same rigorous user privacy standards we’ve always held — in other words, no humans reading your email. This means researchers have to get machine learning to work on a data set that they themselves cannot read, which is a little like trying to solve a puzzle while blindfolded — but a challenge makes it more interesting!
The Selective Laziness of Reasoning — Among those participants who accepted the manipulation and thus thought they were evaluating someone else’s argument, more than half (56% and 58%) rejected the arguments that were in fact their own. Moreover, participants were more likely to reject their own arguments for invalid than for valid answers. This demonstrates that people are more critical of other people’s arguments than of their own, without being overly critical: They are better able to tell valid from invalid arguments when the arguments are someone else’s rather than their own.
How Big is the Gig Economy? (Medium) — this is one example in which the Labor Department and Bureau of Labor Statistics really have shirked their responsibility to try and assess the size and growth of this dynamic shift to our economy.
The Twelve Networking Truths — RFC1925 is channeling the epigram-leaking protagonist of Robert Heinlein’s Time Enough for Love. It is easier to move a problem around (for example, by moving the problem to a different part of the overall network architecture) than it is to solve it. This is true for most areas of life: generally easier to make it someone else’s problem than to solve it.
The Decay of Twitter (The Atlantic) — In other words, on Twitter, people say things that they think of as ephemeral and chatty. Their utterances are then treated as unequivocal political statements by people outside the conversation. Because there’s a kind of sensationalistic value in interpreting someone’s chattiness in partisan terms, tweets “are taken up as magnum opi to be leapt upon and eviscerated, not only by ideological opponents or threatened employers but by in-network peers.”
Anti-Caching (PDF) — paper outlining a clever reframing of the database strategy of keeping frequently accessed things in-memory, namely pushing to disk the things that won’t be accessed … aka, “anti-caching.”
The Rating Game (Verge) — Until companies release ratings data, we can’t know for certain whether this is true, but a study of Airbnb users found that black hosts get less money for similar listings than white hosts, and another study found that white taxi drivers get higher tips than black ones. There’s no reason such biases wouldn’t carry over to ratings.
Singa — Apache distributed deep learning platform turns 1.0.