Four short links: 6 May 2016

Four short links: 6 May 2016

Apple Music UX, Awesome Tensorflow, DNS Chokepoint, and Open Source Bibliometrics

  1. Apple Stole My Music, No SeriouslyAmber relayed to me that she’s had to suffer through many calls from people who cancelled their Apple Music subscription after the free, three-month trial, only to discover that all of their own music files had been deleted and there was no way to get them back. It seemed like a good idea at the time, I’m sure. The product manager said “no, we’ll make them click through a warning, it’ll be fine. The service is amazing, nobody will go back.” I also find the pro/am distinction interesting: anyone who is serious about a medium despises the tools for managing their collection.
  2. Awesome Tensorflow… a curated list of awesome TensorFlow experiments, libraries, and projects.
  3. Elsevier Shuts Down a Sci-Hub Domain — DNS proving a coarse-grained but effective chokepoint, the Web’s app store single-throat-to-choke. Sure can still go straight to IP address, but that’s for nerds not normals.
  4. OpenBR — open source biometrics.

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Four short links: 5 May 2016

Four short links: 5 May 2016

Giphy Pro, Harvesting Robots, Network Ethics, and Music Transcription

  1. Giphy Wants All the GIFs (Backchannel) — they’re licensing legit high-res metadata-rich GIFs from content producers, wanting to become a real search engine. The description of metadata problems on user contributions is interesting. GIF tags were incredibly spammy (“every teenage kid tags everything ‘One Direction’ and ‘Bieber,’” gripes Chung), and many of the GIFs themselves were low-quality due to file-size limits on popular sites such as Reddit and Tumblr. And there was a ton of porn. They were forced to manually clean it up, adding good metadata and using Mechanical Turk to get rid of the NSFW files.
  2. Sweeper Robot — project to build sweet pepper harvesting robot. (via RoboHub)
  3. Workshop on Ethics in Networked Systems Research (SIGCOMM) — it’s about ethics in networked systems research.
  4. Music Transcription Modelling and Composition using Deep Learning (gitxiv) — We build and train LSTM networks using approximately 23,000 music transcriptions expressed with a high-level vocabulary (ABC notation), and use them to generate new transcriptions. With source.

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Four short links: 3 May 2016

Four short links: 3 May 2016

NHS Data Sharing, Underactuated Robotics, April Robotics Numbers, and The Counterfactual Internet

  1. NHS Data Sharing (Ben Goldacre) — as this project lands, we’re all becoming rapidly aware that incompetence, malice and creepiness around confidential data is policed with a worryingly light touch. Ben is scrupulously fair with the benefits and the risks, as clear on the state-of-the-art limitations for data sharing as the opportunities. We have a golden opportunity in the UK, with 60 million people cared for in one glorious NHS.
  2. Underactuated Robotics — MIT coursenotes, forming a working draft of a book is about building robots that move with speed, efficiency, and grace. I believe that this can only be achieve[d] through a tight coupling between mechanical design, passive dynamics, and nonlinear control synthesis. Therefore, these notes contain selected material from dynamical systems theory, as well as linear and nonlinear control.
  3. April Sees Robotics Investment Up (Robohub) — April was a big month for investing in robotics – 19 companies were funded to the tune of $175 million vs. $15.8M in January, $18.6M in February, and $45.4M in March. Four companies were acquired with 3 of the 4 reporting selling prices totaling $422 million.
  4. Inevitability in Technology (Ben Evans) — We think of the portal model as a dead-end, but half a billion Chinese Internet users suggest that it could have been otherwise. The Chinese internet is a great way to challenge your thinking on what’s inevitable in technology – it’s a living counterfactual.

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Four short links: 2 May 2016

Four short links: 2 May 2016

AI Values, Grokking Live Video, Teaching the Future, and Service Workers are the Future

  1. Digital GeniesThe worst thing is a machine that has the wrong values, but is absolutely convinced it has the right ones, because then there’s nothing you can do to divert it from the path it thinks it’s supposed to be following. But if it’s uncertain about what it’s supposed to be following, a lot of the issues become easier to deal with because then the machine says, OK, I know that I’m supposed to be optimizing human values, but I don’t know what they are. It’s precisely this uncertainty that makes the machine safer, because it’s not single minded in pursuing its objectives. It allows itself to be corrected.
  2. Twitter’s AI for Live Video (MIT TR) — deep learning to recognise activity and objects in videos, so Periscope live streams can be searched for and found. I imagine there’s a large portion of the deep learning devoted to forbidden pink.
  3. Teach the Future — materials to “teach the future as we teach the past”, for students in secondary or later. (via Stuart Candy)
  4. Well-Crafted Websites (Adrian Holovaty) — It’s clear to me, studying the history, that service workers are the next big “well-crafted” hint. The signs and similarities are all there. Today, they’re used mostly by fringe sites, in an experimental fashion. It’s inevitable that in a short generation they’ll become common and expected.

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Four short links: 29 April 2016

Four short links: 29 April 2016

AI Gym, Open Sourced Xamarin, History Mining, and Club Economics

  1. OpenAI GymA toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents everything from walking to playing games like Pong or Go.
  2. Open Xamarin — the Xamarin tools are now all MIT-licensed, after the Microsoft acquisition. And show no signs of being abandoned.
  3. Text-Mining the History of MedicineIn this article, we present our efforts to overcome the various challenges faced in the semantic analysis of published historical medical text dating back to the mid 19th century.
  4. A Journal Is a Club (Cameron Neylon) — I’ve been frustrated for a long time with traditional economic analyses of scholarly publishing. They don’t seem to explain what actually happens, and fail to capture critical aspects of what is going on. The lens of club economics seems like it might help to capture more of the reality of what is going on.

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Four short links: 28 April 2016

Four short links: 28 April 2016

Questioning Physical Affordances, Market Solution to Peer Review, Automating Engineering Away, and Data Metaphors

  1. The Shape of Things (Tom Coates) — In fact it’s this problem of what’s most intuitive that gives me most pause for tangible computing generally. The assumption from many of these thinkers is that making an interface that’s physical makes it inherently more intuitive. But I don’t buy that physical affordances alone will make it immediately obvious what a smart connected object is for. Sure, you pick up a hammer and you immediately want to hit something (or maybe that’s just me) — but is that true of a smart hammer?
  2. Improving the Peer Review Process: A Proposed Market System (PDF) — We thus suggest a more efficient and integrity-preserving system based on an open two-sided market in which buyers and sellers of peer review services would both be subject to a set of recursive quality indicators. We lay out key features we think would be important to reduce the opportunities for gaming and that improve the signals about the societal value of a contribution. Cool story bro, but until academics are rewarded financially/professionally for publishing in a Better System, most will accept/route-around the current system.
  3. Are Engineers Designing Their Robotic Replacements? — yes, and that’s the exciting part of software engineering right now.
  4. Metaphors of Data, a Reading ListThe goal in assembling this list was to catalog resources that are helpful in unpacking and critiquing different metaphors, ranging from the hype around data as the new oil to less common (and perhaps more curious) formulations, such as data as sweat or toxic waste.

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