Four short links: 2 May 2017
Elon Musk, Trump's Tech Group, 3D-Printing Buildings, and Great Face Models
- Elon Musk Interviewed at TED — looking at tunneling technology, it turns out that in order to make a tunnel, you have to — in order to seal against the water table, you’ve got to typically design a tunnel wall to be good to about five or six atmospheres. So, to go to vacuum is only one atmosphere, or near-vacuum. So, actually, it sort of turns out that automatically, if you build a tunnel that is good enough to resist the water table, it is automatically capable of holding vacuum. […] November or December of this year, we should be able to go all the way from a parking lot in California to a parking lot in New York, no controls touched at any point during the entire journey.[…] It’s never going to be perfect. No system is going to be perfect, but if you say it’s perhaps — the car is unlikely to crash in a hundred lifetimes, or a thousand lifetimes, then people are like, OK, wow, if I were to live a thousand lives, I would still most likely never experience a crash, then that’s probably OK.
- President Trump’s New Tech Group to ‘Transform and Modernize’ the U.S. Government — because nothing is more Silicon Valley than reinventing the wheel and claiming it’s because of your genius.
- MIT’s 3D Printing for Buildings — Unlike typical 3-D printing systems, most of which use some kind of an enclosed, fixed structure to support their nozzles and are limited to building objects that can fit within their overall enclosure, this free-moving system can construct an object of any size. As a proof of concept, the researchers used a prototype to build the basic structure of the walls of a 50-foot-diameter, 12-foot-high dome—a project that was completed in less than 14 hours of “printing” time.
- Large-Scale 3D Morphable Models — a 3D Morphable Model (3DMM) automatically constructed from 9663 distinct facial identities. To the best of our knowledge, LSFM is the largest-scale Morphable Model ever constructed, containing statistical information from a huge variety of the human population. Matched with the paper Face Normals “in-the-wild” using Fully Convolutional Networks (PDF). The software is open source. (via Science Mag.)
