"education" entries

Four short links: 13 April 2016

Four short links: 13 April 2016

Gesture Learner, Valuing Maintainers, Google's CS Education, and AI Threats

  1. focusmotion.iothe world’s first machine learning SDK to track, learn, and analyze human motion on any sensor, on any OS, on any platform. You (or your users) train it on what combination of sensor patterns to label as a particular gesture or movement, and then it’ll throw those labels whenever.
  2. How Maintainers, not Innovators, Make the World Turn (City Lab) — cf Deb Chachra’s Why I Am Not a Maker and everything Warren Buffett ever wrote about investing in boring businesses. It’s nice to realize that we’ve gone from “you’d be crazy to throw your career away and join a startup” to “hey, established industry isn’t bad, either, you know.”
  3. Google CS Education — all their tools and resources for CS education in one spot.
  4. Will The Proliferation of Affordable AI Decimate the Middle Class? (Alex Tabarrok) — I hadn’t heard this done before, but he steps away from the A in AI to ask whether greater natural intelligence would threaten the middle class in the same way—e.g., from rising India and China.

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Four short links: 28 March 2016

Four short links: 28 March 2016

Holoportation, Filter Your Bot, Curriculum for the Future, and Randomized Control Trials for Policy

  1. Holoportation (YouTube) — video of teleconferencing with the Hololens. I hope my avatar wears more pants than I do.
  2. Wordfilter — package to filter out slurs and the kinds of things you don’t want your bot saying on Twitter. (via How Not to Make a Racist Bot)
  3. Curriculum For the Future (iTunes) — in game form, you get to figure out how to sell your preferred curriculum (“maker!”) to the parents and politicians who care about different things. Similar game mechanic to Win the White House from Sandra Day O’Connor’s iCivics.
  4. Test, Learn, Adapt: Developing Public Policy with Randomized Controlled Trials (PDF) — 2012 paper from the UK Cabinet Office talking about running real randomized control trials of policy. (I’d like to be part of one that looks at better health care!)
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Four short links: 14 March 2016

Four short links: 14 March 2016

Measure What Matters, Broken Laws, Password Recovery Questions, and 3D Object Tracking

  1. What Thomas Hardy Taught MeIn educational research, perhaps the greatest danger lies in thinking “that which I cannot measure is not real.” The disruption fetishists have amplified this danger, now evincing the attitude “teaching that cannot be said to lead to the immediate acquisition of rote, mechanical skills has no value.” But absolutely every aspect of my educational journey — as a student, as a teacher, and as a researcher — demonstrates the folly of this approach to learning. (via Dan Meyer)
  2. Why Anti-Money Laundering Laws and Poorly Designed Copyright Laws Are Similar and Should be Revised (Joi Ito) — Just like with the Internet, weaknesses in networks like the blockchain propagate to countries and regions where privacy risks to users could cause significant risks to human rights workers, journalists, or anyone who questions authority. The conversation on creating new AML and KYC laws for new financial systems like bitcoin and blockchain needs to be a global one.
  3. Secrets, Lies, and Account Recovery: Lessons from the Use of Personal Knowledge Questions at Google — Adrian Colyer summarizes a paper from Google. Using a crowdsourcing service, the authors asked 1,000 users to answer the ‘Favourite Food’ and ‘Father’s middle name’ questions. This took less than a day and cost $100. […] Using a single guess, it turns out, you have a 19.7% chance of guessing an English-speaking users’ answer to the favourite food.
  4. Clever MEMS 3D Object Tracking — early Oculus engineer has invented a nifty way to track a tagged object in 3D space. Worth reading for the description of how it works.
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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: 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: 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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Four short links: 25 January 2016

Four short links: 25 January 2016

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

  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. Gizmoa 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.
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Four short links: 22 January 2016

Four short links: 22 January 2016

Open Source Ultrasound, Deep Learning MOOC, Corp Dev Translation, and Immersive at Sundance

  1. Murgen — open source open hardware ultrasound.
  2. Udacity Deep Learning MOOC — platform is Google’s TensorFlow.
  3. CorpDev Translation“We’ll continue to follow your progress.” Translation: We’ll reach back out when we see you haven’t raised more money and you are probably more desperate because of your shorter runway.
  4. 8i Take Immersive Tech to Sundance8i’s technology lets filmmakers capture entire performances with off-the-shelf cameras and then place them in pre-existing environments, creating a fully navigable 3-D VR movie that’s far more immersive than the 360-degree videos most have seen.
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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

  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 MaterialsWe 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.
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