"open source" entries

Four short links: 15 February 2016

Four short links: 15 February 2016

Deep Learning Analogies, IoT Privacy, Robot Numbers, and App Economy

by Nat Torkington | @gnat | +Nat Torkington | February 15, 2016
  1. Deep Visual Analogy-Making (PDF) — In this paper, we develop a novel deep network trained end-to-end to perform visual analogy making, which is the task of transforming a query image according to an example pair of related images. Open source code from the paper also available.
  2. Samsung’s TV and Privacy Gets More Awkward — Samsung has now issued a new statement clarifying how the voice activation feature works. “If a consumer consents and uses the voice recognition feature, voice data is provided to a third party during a requested voice command search,” Samsung said in a statement. “At that time, the voice data is sent to a server, which searches for the requested content then returns the desired content to the TV.” It only seems creepy until you give in and nothing bad happens, then you normalise the creepy.
  3. 2015 Robot Numbers (RoboHub) — The Robotic Industries Association (RIA), representing North American robotics, reported […] 2015 set new records and showed a 14% increase in units and 11% in dollars over 2014. The automotive industry was the primary growth sector, with robot orders increasing 19% year over year. Non-automotive robot orders grew at 5%.
  4. Mozilla, Caribou Digital Release Report Exploring the Global App Economy (Mark Surman) — The emerging markets are the 1% — meaning, they earn 1% of total app economy revenue. 95% of the estimated value in the app economy is captured by just 10 countries, and 69% of the value is captured by just the top three countries. Excluding China, the 19 countries considered low- or lower-income accounted for only 1% of total worldwide value. Developers in low-income countries struggle to export to the global stage. About one-third of developers in the sample appeared only in their domestic market.

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

by Nat Torkington | @gnat | +Nat Torkington | February 11, 2016
  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)
Four short links: 8 February 2016

Four short links: 8 February 2016

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

by Nat Torkington | @gnat | +Nat Torkington | February 8, 2016
  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 Together — Researchers 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. MyBinder — turn a GitHub repo into a collection of interactive notebooks powered by Jupyter and Kubernetes.
Four short links: 5 February 2016

Four short links: 5 February 2016

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

by Nat Torkington | @gnat | +Nat Torkington | February 5, 2016
  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.
Four short links: 27 January 2016

Four short links: 27 January 2016

Generative Text, Open Source Agriculture, Becoming Better, and GA Slackbot

by Nat Torkington | @gnat | +Nat Torkington | January 27, 2016
  1. Improv — a javascript library for generative text.
  2. The Food Computer (MIT) — open source controlled-environment agriculture technology platform that uses robotic systems to control and monitor climate, energy, and plant growth inside of a specialized growing chamber. Climate variables such as carbon dioxide, air temperature, humidity, dissolved oxygen, potential hydrogen, electrical conductivity, and root-zone temperature are among the many conditions that can be controlled and monitored within the growing chamber. Operational energy, water, and mineral consumption are monitored (and adjusted) through electrical meters, flow sensors, and controllable chemical dosers throughout the growth period. (via IEEE Spectrum)
  3. 10 Golden Rules for Becoming a Better Programmer — what are your 10 rules for being better in your field? If you haven’t built a list, then you aren’t thinking hard enough about what you do.
  4. Statsbot — Google Analytics bot for Slack from NewRelic.
Four short links: 25 January 2016

Four short links: 25 January 2016

Company Mortality, Geoffrey West Profile, Microservice Toolkit, and Problem-Free Activities

by Nat Torkington | @gnat | +Nat Torkington | January 25, 2016
  1. The Mortality of Companies — Geoffrey West paper: we show that the mortality of publicly traded companies manifests an approximately constant hazard rate over long periods of observation. This regularity indicates that mortality rates are independent of a company’s age. We show that the typical half-life of a publicly traded company is about a decade, regardless of business sector.
  2. The Fortune 500 Teller — profile of Geoffrey West. (via Roger Dennis)
  3. Gizmo — a microservice toolkit in Golang from NYT. (via InfoQ)
  4. Intellectual Need and Problem-Free Activity in the Mathematics Classroom (PDF) — Although this is not an empirical study, we use data from observed high school algebra classrooms to illustrate four categories of activity students engage in while feeling little or no intellectual need. We present multiple examples for each category in order to draw out different nuances of the activity, and we contrast the observed situations with ones that would provide various types of intellectual need. Finally, we offer general suggestions for teaching with intellectual need.
Four short links: 20 January 2016

Four short links: 20 January 2016

Rules-Based Distributed Code, Open Source Face Recognition, Simulation w/Emoji, and Berkeley's AI Materials

by Nat Torkington | @gnat | +Nat Torkington | January 20, 2016
  1. Experience with Rules-Based Programming for Distributed Concurrent Fault-Tolerant Code (A Paper a Day) — To demonstrate applicability outside of the RAMCloud system, the team also re-wrote the Hadoop Map-Reduce job scheduler (which uses a traditional event-based state machine approach) using rules. The original code has three state machines containing 34 states with 163 different transitions, about 2,250 lines of code in total. The rules-based re-implementation required 19 rules in 3 tasks with a total of 117 lines of code and comments. Rules-based systems are powerful and underused.
  2. OpenFace — open source face recognition software using deep neural networks.
  3. Simulating the World in Emoji — fun simulation environment in the browser.
  4. Berkeley’s Intro-to-AI Materials — We designed these projects with three goals in mind. The projects allow students to visualize the results of the techniques they implement. They also contain code examples and clear directions, but do not force students to wade through undue amounts of scaffolding. Finally, Pac-Man provides a challenging problem environment that demands creative solutions; real-world AI problems are challenging, and Pac-Man is, too.
Four short links: 19 January 2016

Four short links: 19 January 2016

Spermbots, Reputation Risks, Lab Robot, and Stack Expansion

by Nat Torkington | @gnat | +Nat Torkington | January 19, 2016
  1. Spermbots — Researchers from the Institute for Integrative Nanosciences at IFW Dresden in Germany have successfully tested tiny, magnetically-driven power suits for individual sperm that can turn them into steerable cyborg “spermbots” that can be remote controlled all the way to the egg. But can they make an underwire bra that the washing machine doesn’t turn into a medieval torture device?
  2. What’s Eating Silicon Valley — In 2014, more Harvard Business School Grads went into technology than into banking for the first time since the dot-com era. […] another reason Wall Street had trouble maintaining goodwill was because of some of the attributes above—hard-charging, too much too soon, parallel reality, money flowing everywhere, rich white guys, etc. The Wall St comparison was new to me, but I can see it as a goodwill risk.
  3. OpenTrons — $3,000 open source personal lab robot for science, with downloadable/shareable protocols.
  4. Why Big Companies Keep Failing: The Stack Fallacy — you’re more likely to succeed if you expand down (to supplant your suppliers) than up (to build the products that are built on top of your product) because you’re a customer of your suppliers, so you know what good product-market fit will look like, but you’re just fantasizing that you can supplant your downstream value.
Four short links: 18 January 2016

Four short links: 18 January 2016

Machine Learning Technical Debt, Audio Matching, Self-Tracking Research, and Baidu's Open Source Deep Learning Code

by Nat Torkington | @gnat | +Nat Torkington | January 18, 2016
  1. Hidden Technical Debt in Machine Learning Systems (PDF) — We explore several ML-specific risk factors to account for in system design. These include boundary erosion, entanglement, hidden feedback loops, undeclared consumers, data dependencies, configuration issues, changes in the external world, and a variety of system-level anti-patterns.
  2. Large-Scale Content-Based Matching of Midi and Audio Files — We present a system that can efficiently match and align MIDI files to entries in a large corpus of audio content based solely on content, i.e., without using any metadata.
  3. Critical Social Research on Self-Tracking — I am currently working on an article that is a comprehensive review of both literatures, in the attempt to outline what each can contribute to understanding self-tracking as an ethos and a practice, and its wider sociocultural implications. Here is a reading list of the work from critical social researchers that I am aware of. Trigger warning: phrases like “The discursive construction of student subjectivities.”
  4. Warp-CTC — Baidu’s open source deep learning code. Connectionist Temporal Classification is a loss function useful for performing supervised learning on sequence data, without needing an alignment between input data and labels.
Four short links: January 15, 2016

Four short links: January 15, 2016

Bitcoin Resolution, Malware Analysis, Website Screw-Ups, and Dronecode.

by Nat Torkington | @gnat | +Nat Torkington | January 15, 2016
  1. The Resolution of the Bitcoin Experiment — If you had never heard about Bitcoin before, would you care about a payments network that: Couldn’t move your existing money; Had wildly unpredictable fees that were high and rising fast; Allowed buyers to take back payments they’d made after walking out of shops, by simply pressing a button (if you aren’t aware of this “feature” that’s because Bitcoin was only just changed to allow it); Is suffering large backlogs and flaky payments; … which is controlled by China; … and in which the companies and people building it were in open civil war?
  2. Malware Analysis Repository — the materials as developed and used by RPISEC to teach Malware Analysis at Rensselaer Polytechnic Institute in Fall 2015.
  3. How Websites Screw Up Experiences (Troy Hunt) — they’re mostly signs of a to-the-death business model.
  4. Dronecode Moves Forward — Linux Foundation’s Dronecode project has 51 members, is used commercially, and has technical working groups looking at camera and gimbal controls; airspace management; and hardware/software interfaces.