Four short links: 9 November 2015

Smart Sensors, Learning Autopilot, Higher Education, and 3D Soccer

  1. Low-Power Deep Learning — it’s a media release for proprietary tech, but interesting that people are working on low-power deep learning neural nets. As Pete Warden noted, this kind of research will be at the center of smart sensors. (via Pete Warden)
  2. Tesla’s Self-Improving Autopilot — it learns when you “rescue” (aka take control back from autopilot), so it’s getting better day by day. Musk said that Model S owners could add ~1 million miles of new data every day, which is helping the company create “high-precision maps.” Navteq, Google Maps, Waze … new map data is still valuable.
  3. The Digital Revolution in Higher Education Has Already Happened (Clay Shirky) — and no-one noticed. I read half of this before going “holy crap this is good, who wrote it?” I’m a Shirky junkie (I bet his laundry lists cite Habermas and the Peace of Westphalia). At the current rate of growth, half the country’s undergraduates will have at least one online class on their transcripts by the end of the decade. This is the new normal. But, As long as we discuss online education as a pedagogic revolution rather than an organizational one, we aren’t even having the right kind of conversation. The dramatic adoption of online education is not mainly a change in the content of classes. It’s a change in the institutional form of college, a demand for more flexibility by students who have to manage the increasingly complicated triangle of work, family, and school.
  4. System Automatically Converts 2-D to 3-D (MIT) — hilarious strategy! They constrained their domain: broadcast soccer games. The MIT and QCRI researchers essentially ran this process in reverse. They set the very realistic Microsoft soccer game “FIFA13” to play over and over again, and used Microsoft’s video-game analysis tool PIX to continuously store screen shots of the action. For each screen shot, they also extracted the corresponding 3-D map. […] For every frame of 2-D video of an actual soccer game, the system looks for the 10 or so screen shots in the database that best correspond to it. Then it decomposes all those images, looking for the best matches between smaller regions of the video feed and smaller regions of the screen shots. Once it’s found those matches, it superimposes the depth information from the screen shots on the corresponding sections of the video feed. Finally, it stitches the pieces back together. Brute-forcing soccer. Ok, perhaps “hilarious” for a certain type of person. I am that person.
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