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: 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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Four short links: 4 February 2016

Four short links: 4 February 2016

Shmoocon Video, Smart Watchstrap, Generalizing Learning, and Dataflow vs Spark

  1. Shmoocon 2016 Videos (Internet Archive) — videos of the talks from an astonishingly good security conference.
  2. TipTalk — Samsung watchstrap that is the smart device … put your finger in your ear to hear the call. You had me at put my finger in my ear. (via WaPo)
  3. Ecorithms — Leslie Valiant at Harvard broadened the concept of an algorithm into an “ecorithm,” which is a learning algorithm that “runs” on any system capable of interacting with its physical environment. Algorithms apply to computational systems, but ecorithms can apply to biological organisms or entire species. The concept draws a computational equivalence between the way that individuals learn and the way that entire ecosystems evolve. In both cases, ecorithms describe adaptive behavior in a mechanistic way.
  4. Dataflow/Beam vs Spark (Google Cloud) — To highlight the distinguishing features of the Dataflow model, we’ll be comparing code side-by-side with Spark code snippets. Spark has had a huge and positive impact on the industry thanks to doing a number of things much better than other systems had done before. But Dataflow holds distinct advantages in programming model flexibility, power, and expressiveness, particularly in the out-of-order processing and real-time session management arenas.
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Four short links: 3 February 2016

Four short links: 3 February 2016

Security Forecast, Machine Learning for Defence, Retro PC Fonts, and Cognitive Psych Research

  1. Software Security Ideas Ahead of Their Time — astonishing email exchange from 1995 presaged a hell of a lot of security work.
  2. Doxxing Sherlock — Cory Doctorow’s ruminations on surveillance, Sherlock, and what he found in the Snowden papers. What he found included an outline of intelligence use of machine learning.
  3. Old-School PC Fonts — definitive collection of ripped-from-the-BIOS fonts from the various types of PCs. Your eyes will ache with nostalgia. (Or, if you’re a young gun, wondering how anybody wrote code with fonts like that) (my terminal font is VT220 because it makes me happy and productive)
  4. Cognitive Load: Brain GemsWe distill the latest behavioural economics & consumer psychology research down into helpful little brain gems.
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Four short links: 2 February 2016

Four short links: 2 February 2016

Fourth Industrial Revolution, Agent System, Evidence-Based Programming, and Deep Learning Service

  1. This is Not the Fourth Industrial Revolution (Slate) — the phrase “the fourth Industrial Revolution” has been around for more than 75 years. It first came into popular use in 1940.
  2. Huginn — MIT-licensed system for building agents that perform automated tasks for you online. They can read the Web, watch for events, and take actions on your behalf. Huginn’s Agents create and consume events, propagating them along a directed graph. Think of it as a hackable Yahoo! Pipes plus IFTTT on your own server.
  3. Evidence-Oriented Programming — design programming language syntax and features based on what research shows works. They tested Perl and Java, found apparently not detectably easier to use for novices than a language that my student at the time, Susanna Kiwala (formerly Siebert), created by essentially rolling dice and picking (ridiculous) symbols at random.
  4. Deep Detect — open source deep learning service.
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Four short links: 1 February 2016

Four short links: 1 February 2016

Curation & Search, Developer Tenure, AI/IA History, and Catapulting Drones

  1. Curation & Search — (Twitter) All curation grows until it requires search. All search grows until it requires curation.—Benedict Evans. (via Lists are the New Search)
  2. Average Developer Tenure (Seattle Times) — The average tenure of a developer in Silicon Valley is nine months at a single company. In Seattle, that length is closer to two years. (via Rands)
  3. An Interview with John Markoff (Robohub) — the interview will give you a flavour of his book, Machines of Loving Grace, a sweet history of AI told through the stories of the people who pioneered and now shape the field.
  4. Catapult Drone Launch (YouTube) — utterly nuts. That’s an SUV off its rear wheels! (via IEEE)
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Four short links: 29 January 2016

Four short links: 29 January 2016

LTE Security, Startup Tools, Security Tips, and Data Fiction

  1. LTE Weaknesses (PDF) — ShmooCon talk about how weak LTE is: a lot of unencrypted exchanges between handset and basestation, cheap and easy to fake up a basestation.
  2. AnalyzoFind and Compare the Best Tools for your Startup it claims. We’re in an age of software surplus: more projects, startups, apps, and tools than we can keep in our heads. There’s a place for curated lists, which is why every week brings a new one.
  3. How to Keep the NSA Out — NSA’s head of Tailored Access Operations (aka attacking other countries) gives some generic security advice, and some interesting glimpses. “Don’t assume a crack is too small to be noticed, or too small to be exploited,” he said. If you do a penetration test of your network and 97 things pass the test but three esoteric things fail, don’t think they don’t matter. Those are the ones the NSA, and other nation-state attackers will seize on, he explained. “We need that first crack, that first seam. And we’re going to look and look and look for that esoteric kind of edge case to break open and crack in.”
  4. The End of Big Data — future fiction by James Bridle.
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Four short links: 28 January 2016

Four short links: 28 January 2016

Augmented Intelligence, Social Network Limits, Microsoft Research, and Google's Go

  1. Chimera (Paper a Day) — the authors summarise six main lessons learned while building Chimera: (1) Things break down at large scale; (2) Both learning and hand-crafted rules are critical; (3) Crowdsourcing is critical, but must be closely monitored; (4) Crowdsourcing must be coupled with in-house analysts and developers; (5) Outsourcing does not work at a very large scale; (6) Hybrid human-machine systems are here to stay.
  2. Do Online Social Media Remove Constraints That Limit the Size of Offline Social Networks? (Royal Society) — paper by Robin Dunbar. Answer: The data show that the size and range of online egocentric social networks, indexed as the number of Facebook friends, is similar to that of offline face-to-face networks.
  3. Microsoft Embedding ResearchTo break down the walls between its research group and the rest of the company, Microsoft reassigned about half of its more than 1,000 research staff in September 2014 to a new group called MSR NExT. Its focus is on projects with greater impact to the company rather than pure research. Meanwhile, the other half of Microsoft Research is getting pushed to find more significant ways it can contribute to the company’s products. The challenge is how to avoid short-term thinking from your research team. For instance, Facebook assigns some staff to focus on long-term research, and Google’s DeepMind group in London conducts pure AI research without immediate commercial considerations.
  4. Google’s Go-Playing AIThe key to AlphaGo is reducing the enormous search space to something more manageable. To do this, it combines a state-of-the-art tree search with two deep neural networks, each of which contains many layers with millions of neuron-like connections. One neural network, the “policy network,” predicts the next move, and is used to narrow the search to consider only the moves most likely to lead to a win. The other neural network, the “value network,” is then used to reduce the depth of the search tree — estimating the winner in each position in place of searching all the way to the end of the game.
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Four short links: 27 January 2016

Four short links: 27 January 2016

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

  1. Improva 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.
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Four short links: 26 January 2016

Four short links: 26 January 2016

Inequality, Conversational Commerce, Minsky Lectures, and Trust vs Transparency

  1. What Paul Graham is Missing About Inequality (Tim O’Reilly) — When a startup doesn’t have an underlying business model that will eventually produce real revenues and profits, and the only way for its founders to get rich is to sell to another company or to investors, you have to ask yourself whether that startup is really just a financial instrument, not that dissimilar to the CDOs of the 2008 financial crisis — a way of extracting value from the economy without actually creating it.
  2. 2016 The Year of Conversational Commerce (Chris Messina) — I really hope that these conversations with companies are better than the state-of-the-art delights of “press 5 to replay” phone hell.
  3. Society of Mind (MIT) — Marvin Minsky’s course, with lectures.
  4. Trust vs Transparency (PDF) — explanation facilities
    can potentially drop both a user’s confidence and make the process of search more stressful.
    Aka “few takers for sausage factory tours.” (via ACM Queue)
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