Four short links: 10 November 2015

TensorFlow Released, TensorFlow Described, Neural Networks Optimized, Cybersecurity as RealPolitik

  1. 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.
  2. 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.
  3. 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.
  4. 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.
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