Nat Torkington

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.

Four short links: 9 March 2016

Four short links: 9 March 2016

Surveillance Capitalism, Spark in Jupyter, Spoofing Fingerprints, and Distributing SSH Keys

  1. The Secrets of Surveillance CapitalismThe assault on behavioral data is so sweeping that it can no longer be circumscribed by the concept of privacy and its contests. […] First, the push for more users and more channels, services, devices, places, and spaces is imperative for access to an ever-expanding range of behavioral surplus. Users are the human nature-al resource that provides this free raw material. Second, the application of machine learning, artificial intelligence, and data science for continuous algorithmic improvement constitutes an immensely expensive, sophisticated, and exclusive 21st century “means of production.” Third, the new manufacturing process converts behavioral surplus into prediction products designed to predict behavior now and soon. Fourth, these prediction products are sold into a new kind of meta-market that trades exclusively in future behavior. The better (more predictive) the product, the lower the risks for buyers, and the greater the volume of sales. Surveillance capitalism’s profits derive primarily, if not entirely, from such markets for future behavior. (via Simon St Laurent)
  2. Thunder — Spark-driven analysis from Jupyter notebooks (open source).
  3. Hacking Mobile Phones Using 2D-Printed Fingerprints (PDF) — equipment costs less than $450, and all you need is a photo of the fingerprint. (like those of government employees stolen en masse last year)
  4. SSHKeyDistribut0r (Github) — A tool to automate key distribution with user authorization […] for sysop teams.
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Four short links: 8 March 2016

Four short links: 8 March 2016

Neural Nets on Encrypted Data, IoT VR Prototype, Group Chat Considered Harmful, and Haptic Hardware

  1. Neutral Nets on Encrypted Data (Paper a Day) — By using a technique known as homohorphic encryption, it’s possible to perform operations on encrypted data, producing an encrypted result, and then decrypt the result to give back the desired answer. By combining homohorphic encryption with a specially designed neural network that can operate within the constraints of the operations supported, the authors of CryptoNet are able to build an end-to-end system whereby a client can encrypt their data, send it to a cloud service that makes a prediction based on that data – all the while having no idea what the data means, or what the output prediction means – and return an encrypted prediction to the client, which can then decrypt it to recover the prediction. As well as making this possible, another significant challenge the authors had to overcome was making it practical, as homohorphic encryption can be expensive.
  2. VR for IoT Prototype (YouTube) — a VR prototype created for displaying sensor data and video streaming in real time from IoT sensors/camera devices designed for rail or the transportation industry.
  3. Is Group Chat Making You Sweat? (Jason Fried) — all excellent points. Our attention and focus are the scarce and precious resources of the 21st century.
  4. How Devices Provide Haptic Feedback — good intro to what’s happening in your hardware.
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Four short links: 7 March 2016

Four short links: 7 March 2016

Trajectory Data Mining, Manipulating Search Rankings, Open Source Data Exploration, and a Linter for Prose.

  1. Trajectory Data Mining: An Overview (Paper a Day) — This is the data created by a moving object, as a sequence of locations, often with uncertainty around the exact location at each point. This could be GPS trajectories created by people or vehicles, spatial trajectories obtained via cell phone tower IDs and corresponding transmission times, the moving trajectories of animals (e.g. birds) fitted with trackers, or even data concerning natural phenomena such as hurricanes and ocean currents. It turns out, there’s a lot to learn about working with such data!
  2. Search Engine Manipulation Effect (PNAS) — Internet search rankings have a significant impact on consumer choices, mainly because users trust and choose higher-ranked results more than lower-ranked results. Given the apparent power of search rankings, we asked whether they could be manipulated to alter the preferences of undecided voters in democratic elections. They could. Read the article for their methodology. (via Aeon)
  3. Keshif — open source interactive data explorer.
  4. proselint — analyse text for sins of usage and abusage.
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Four short links: 4 March 2016

Four short links: 4 March 2016

Snapchat's Business, Tracking Voters, Testing for Discriminatory Associations, and Assessing Impact

  1. How Snapchat Built a Business by Confusing Olds (Bloomberg) — Advertisers don’t have a lot of good options to reach under-30s. The audiences of CBS, NBC, and ABC are, on average, in their 50s. Cable networks such as CNN and Fox News have it worse, with median viewerships near or past Social Security age. MTV’s median viewers are in their early 20s, but ratings have dropped in recent years. Marketers are understandably anxious, and Spiegel and his deputies have capitalized on those anxieties brilliantly by charging hundreds of thousands of dollars when Snapchat introduces an ad product.
  2. Tracking VotersOn the night of the Iowa caucus, Dstillery flagged all the [ad network-mediated ad] auctions that took place on phones in latitudes and longitudes near caucus locations. It wound up spotting 16,000 devices on caucus night, as those people had granted location privileges to the apps or devices that served them ads. It captured those mobile ID’s and then looked up the characteristics associated with those IDs in order to make observations about the kind of people that went to Republican caucus locations (young parents) versus Democrat caucus locations. It drilled down further (e.g., ‘people who like NASCAR voted for Trump and Clinton’) by looking at which candidate won at a particular caucus location.
  3. Discovering Unwarranted Associations in Data-Driven Applications with the FairTest Testing Toolkit (arXiv) — We describe FairTest, a testing toolkit that detects unwarranted associations between an algorithm’s outputs (e.g., prices or labels) and user subpopulations, including sensitive groups (e.g., defined by race or gender). FairTest reports statistically significant associations to programmers as association bugs, ranked by their strength and likelihood of being unintentional, rather than necessary effects. See also slides from PrivacyCon. Source code not yet released.
  4. Inferring Causal Impact Using Bayesian Structural Time-Series Models (Adrian Colyer) — understanding the impact of an intervention by building a predictive model of what would have happened without the intervention, then diffing reality to that model.
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Four short links: 3 March 2016

Four short links: 3 March 2016

Tagging People, Maintenance Anti-Pattern, Insourced Brains, and Chat UI

  1. Human Traffickers Using RFID Chips (NPR) — It turns out this 20-something woman was being pimped out by her boyfriend, forced to sell herself for sex and hand him the money. “It was a small glass capsule with a little almost like a circuit board inside of it,” he said. “It’s an RFID chip. It’s used to tag cats and dogs. And someone had tagged her like an animal, like she was somebody’s pet that they owned.”
  2. Software Maintenance is an Anti-PatternGovernments often use two anti-patterns when sustaining software: equating the “first release” with “complete” and moving to reduce sustaining staff too early; and how a reduction of staff is managed when a reduction in budget is appropriate.
  3. Cloud Latency and Autonomous Robots (Ars Technica) — “Accessing a cloud computer takes too long. The half-second time delay is too noticeable to a human,” says Ishiguro, an award-winning roboticist at Osaka University in Japan. “In real life, you never wait half a second for someone to respond. People answer much quicker than that.” Tech moves in cycles, from distributed to centralized and back again. As with mobile phones, the question becomes, “what is the right location for this functionality?” It’s folly to imagine everything belongs in the same place.
  4. Chat as UI (Alistair Croll) — The surface area of the interface is almost untestable. The UI is the log file. Every user interaction is also a survey. Chat is a great interface for the Internet of Things. It remains to be seen how many deep and meaningfuls I want to have with my fridge.
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Four short links: 2 March 2016

Four short links: 2 March 2016

Sensing Cognitive Load, Boring is Good, Replicating SQLite, and Intro to Autonomous Robots

  1. An Adaptive Learning Interface that Adjusts Task Difficulty based on Brain State (PDF) — using blood flow to measure cognitive load, this tool releases new lessons to you when you’re ready for them. The system measures blood flow using functional near-infrared spectroscopy (fNIRS). Increased activation in an area of the brain results in increased levels of oxyhemoglobin. These changes can be measured by emitting frequencies of near-infrared light around 3 cm deep into the brain tissue and measuring the light attenuation caused by levels of oxyhemoglobin. I think we all want a widget on our computer that says “your brain is full, go offline to recover,” if only to validate naptime.
  2. Deploying SoftwareYour deploys should be as boring, straightforward, and stress-free as possible. cf Maciej Ceglowski’s “if you find it interesting, it doesn’t belong in production.”
  3. Replicating SQLite Using Raftrqlite is written in Go and uses Raft to achieve consensus across all the instances of the SQLite databases. rqlite ensures that every change made to the database is made to a quorum of SQLite files, or none at all.
  4. An Introduction to Autonomous RobotsAn open textbook focusing on computational principles of autonomous robots. CC-NC-ND and for sale via Amazon.
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Four short links: 1 March 2016

Four short links: 1 March 2016

Phone Kit, Circular Phone, TensorFlow Intro, and Change Motivation

  1. Seeed RePhoneopen source and modular phone kit.
  2. Cyrcle — prototype round phone, designed by women for women. It’s clearly had a bit more thought put into it than the usual “pink it and shrink it” approach … circular to fit in smaller and shaped pockets, and software features strict notification controls: the device would only alert you to messages or updates from an inner circle.
  3. TensorFlow for Poets (Pete Warden) — I want to show how anyone with a Mac laptop and the ability to use the Terminal can create their own image classifier using TensorFlow, without having to do any coding.
  4. Finding the Natural Motivation for Change (Pia Waugh) — you can force certain behaviour changes through punishment or reward, but if people aren’t naturally motivated to make the behaviour change themselves then the change will be both unsustainable and minimally implemented. Amen!
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Four short links: 29 February 2016

Four short links: 29 February 2016

Robots & Decisions, Brain Modem, Distributed Devops Clue, and Robots in Law

  1. Learning Models for Robot Decision Making (YouTube) — a talk at the CMU Robotics Institute.
  2. Brain Modema tiny sensor that travels through blood vessels, lodges in the brain and records neural activity. The “stentrode” (stent + electrode) is the size of a paperclip, and Melbourne researchers (funded by DARPA) have made the first successful animal trials.
  3. The Past and Future are Here, It’s Just Not Evenly Distributed (Usenix) — slides, audio and video.
  4. Robots in American LawThis article closely examines a half century of case law involving robots. […] The first set highlights the role of robots as the objects of American law. Among other issues, courts have had to decide whether robots represent something “animate” for purposes of import tariffs, whether robots can “perform” as that term is understood in the context of a state tax on performance halls, and whether a salvage team “possesses” a shipwreck it visits with an unmanned submarine. (via BoingBoing)
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Four short links: 26 February 2016

Four short links: 26 February 2016

High-Performing Teams, Location Recognition, Assessing Computational Thinking, and Values in Practice

  1. What Google Learned From Its Quest to Build the Perfect Team (NY Times) — As the researchers studied the groups, however, they noticed two behaviors that all the good teams generally shared. First, on the good teams, members spoke in roughly the same proportion […] Second, the good teams all had high ‘‘average social sensitivity’’ — a fancy way of saying they were skilled at intuiting how others felt based on their tone of voice, their expressions, and other nonverbal cues.
  2. Photo Geolocation with Convolutional Neural Networks (arXiv) — 377MB gets you a neural net, trained on geotagged Web images, that can suggest location of the image. From MIT TR’s coverage: To measure the accuracy of their machine, they fed it 2.3 million geotagged images from Flickr to see whether it could correctly determine their location. “PlaNet is able to localize 3.6% of the images at street-level accuracy and 10.1% at city-level accuracy,” say Weyand and co. What’s more, the machine determines the country of origin in a further 28.4% of the photos and the continent in 48.0% of them.
  3. Assessing the Development of Computational Thinking (Harvard) — we have relied primarily on three approaches: (1) artifact-based interviews, (2) design scenarios, and (3) learner documentation. (via EdSurge)
  4. Values in Practice (Camille Fournier) — At some point, I realized there was a pattern. The people in the company who were beloved by all, happiest in their jobs, and arguably most productive, were the people who showed up for all of these values. They may not have been the people who went to the best schools, or who wrote the most beautiful code; in fact, they often weren’t the “on-paper” superstars. But when it came to the job, they were great, highly in-demand, and usually promoted quickly. They didn’t all look the same, they didn’t all work in the same team or have the same skill set. Their only common thread was that they didn’t have to stretch too much to live the company values because the company values overlapped with their own personal values.
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Four short links: 25 February 2016

Four short links: 25 February 2016

Security Advice, Common Deep Learning Interface, React Text Editing, and Sexy Docs

  1. Free Security Advice (grugq) — chap wearies of handing out security advice, so gathers it and shares for all.
  2. TensorFuseCommon interface for Theano, CGT, and TensorFlow.
  3. Draft.jsa framework for building rich text editors in React, powered by an immutable model and abstracting over cross-browser differences.
  4. Dexya free-form literate documentation tool for writing any kind of technical document incorporating code. Dexy helps you write correct documents, and to easily maintain them over time as your code changes.
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