Four short links: 12 February 2016

Four short links: 12 February 2016

Slack's Voice, Accessible Experiences, IoT Design, and What I Learned

  1. Webstock: Bug Fixes & Minor Improvements — notes from Anna Pickard’s talk about being the voice of Slack, recorded by Luke Wroblewski.
  2. Webstock: The Map & The Territory — notes from Ethan Marcotte’s talk about making accessible experiences, recorded by Luke Wroblewski.
  3. Webstock: The Shape of Things — notes from Tom Coates’s talk about designing for the Internet of Things, recorded by Luke Wroblewski.
  4. Today I LearnedA collection of concise write-ups on small things I learn day to day across a variety of languages and technologies. These are things that don’t really warrant a full blog post.
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Four short links: 11 February 2016

Four short links: 11 February 2016

Surviving Crashes, Thumbs-Up Thumbs-Down Learning, Faster Homomorphic Encryption, and Nerdy V-Day Cards

  1. All File Systems are Not Created Equal: On the Complexity of Crafting Crash Consistent Applications (Paper a Day) — an important subject for me. BOB, the Block Order Breaker, is used to find out what behaviours are exhibited by a number of modern file systems that are relevant to building crash consistent applications. ALICE, the Application Level Intelligent Crash Explorer, is then used to explore the crash recovery behaviour of a number of applications on top of these file systems.
  2. BinaryNet: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1 (Arxiv) — instead of complex positive/negative floating-point weights, this uses +1 and -1 (which I can’t help but think of as “thumbs up”, “thumbs down”) to get nearly state-of-the-art results because a run-time, BinaryNet drastically reduces memory usage and replaces most multiplications by 1-bit exclusive-not-or (XNOR) operations, which might have a big impact on both general-purpose and dedicated Deep Learning hardware. GPLv2 code available.
  3. Microsoft Speeds Up Homomorphic Encryption (The Register) — homomorphic encryption lets databases crunch data without needing keys to decode it.
  4. Nerdy Valentine Cards (Evil Mad Scientist) — for a nerd in your life. (via Cory Doctorow)
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Four short links: 10 February 2016

Four short links: 10 February 2016

Bitcoin Textbook, Brain Books, Post-Quantum Crypto, and Amazon's Game Engine

  1. Princeton Bitcoin Book (PDF) — The Coursera course accompanying this book had 30,000 students in its first version, and it was a success based on engagement and end-of-course feedback. Large introduction to Bitcoin from Princeton. (via Cory Doctorow)
  2. A Quartet of Complementary Brain Books (Vaughan Bell) — The books have been chosen to complement each other and the idea is that if you read all four, you should have a solid grounding in modern cognitive neuroscience and beyond.
  3. NIST Report on Post-Quantum Cryptography (PDF) — in case you missed it, “post-quantum crypto” is “existing crypto relies on how hard it is to find the prime factors of large numbers, of which we suspect quantum computers may make a mockery. Wut to do?” The goal of post-quantum cryptography (also called quantum-resistant cryptography) is to develop cryptographic systems that are secure against both quantum and classical computers, and can interoperate with existing communications protocols and networks.
  4. Amazon Lumberyarda free, cross-platform, 3D game engine for you to create the highest-quality games, connect your games to the vast compute and storage of the AWS Cloud, and engage fans on Twitch. From Amazon.
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Four short links: 9 February 2016

Four short links: 9 February 2016

Collaborative Mario Agents, ElasticSearch at Scale, Anomaly Detection, Robotics Experiment

  1. Social Intelligence in Mario Bros (YouTube) — collaborative agents built by cognitive AI researchers … they have drives, communicate, learn from each other, and solve problems. Oh, and the agents are Mario, Luigi, Yoshi, and Toad within a Super Mario Brothers clone. No code or papers about it on the research group’s website yet, just a YouTube video and a press release on the university’s website, so appropriately adjust your priors for imminent world destruction at the hands of a rampaging super-AI. (via gizmag)
  2. How we Monitor and Run ElasticSearch at Scale (SignalFx) — sweet detail on metrics, dashboards, and alerting.
  3. Simple Anomaly Detection for Weekly PatternsRule-based heuristics do not scale and do not adapt easily, especially if we have thousands of alarms to set up. Some statistical approach is needed that is generic enough to handle many different metric behaviours.
  4. How to Design a Robotics Experiment (Robohub) — although there are many good experimental scientists in the robotic community, there has not been uniformly good experimental work and reporting within the community as a whole. This has advice such as “the five components of a well-designed experiment.”
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Four short links: 8 February 2016

Four short links: 8 February 2016

Experimental Support, Coding Books, Bad Decisions, and GitHub to Jupyter

  1. Elemental Machines — Boston startup fitting experiments & experimenters with sensors, deep learning to identify problems (vibration, humidity, etc.) that could trigger experimental failure. [C]rucial experiments are often delayed by things that seem trivial in retrospect. “I talked to my friends who worked in labs,” Iyengar says. “Everyone had a story to tell.” One scientist’s polymer was unstable because of ultraviolet light coming through a nearby window, he says; that took six months to debug. Another friend who worked at a pharmaceutical company was testing drug candidates in mice. The results were one failure after another, for months, until someone figured out that the lab next door was being renovated, and after-hours construction was keeping the mice awake and stressing them out. (that quote from Xconomy)
  2. Usborne Computer and Coding Books — not only do they have sweet Scratch books for kids, they also have their nostalgia-dripping 1980s microcomputer books online. I still have a pile of my well-loved originals.
  3. Powerful People are Terrible at Making Decisions TogetherResearchers from the Haas School of Business at the University of California, Berkeley, undertook an experiment with a group of health care executives on a leadership retreat. They broke them into groups, presented them with a list of fictional job candidates, and asked them to recommend one to their CEO. The discussions were recorded and evaluated by independent reviewers. The higher the concentration of high-ranking executives, the more a group struggled to complete the task. They competed for status, were less focused on the assignment, and tended to share less information with each other.
  4. MyBinderturn a GitHub repo into a collection of interactive notebooks powered by Jupyter and Kubernetes.
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Four short links: 5 February 2016

Four short links: 5 February 2016

Signed Filesystem, Smart Mirror, Deep Learning Tuts, and CLI: Miami

  1. Introducing the Keybase Filesystem — love that crypto is making its way into the filesystem.
  2. DIY Smart Bathroom Mirror — finally, someone is building this science-fiction future! (via BoingBoing)
  3. tensorflow tutorials — for budding deep learners.
  4. clmystery — a command-line murder mystery.
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