In a first, a driverless bus will now have to undergo real world traffic while shuttling passengers as a public trial on Dutch roads begins.
While Google and Uber are currently experimenting with self-driving cars, other companies are adapting the same idea to public transportation. Trials for driverless buses and trains are currently ongoing across the world.
But now, a new milestone has been reached.
The game of Go has long been viewed as the most challenging of classic games for artificial intelligence due to its enormous search space and the difficulty of evaluating board positions and moves.
Google DeepMind introduced a new approach to computer Go with their program, AlphaGo, that uses value networks to evaluate board positions and policy networks to select moves. These deep neural networks are trained by a novel combination of supervised learning from human expert games, and reinforcement learning from games of self-play. Without any lookahead search, the neural networks play Go at the level of state-of-the-art Monte-Carlo tree search programs that simulate thousands of random games of self-play. DeepMind also introduce a new search algorithm that combines Monte-Carlo simulation with value and policy networks. Using this search algorithm, our program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the European Go champion by 5 games to 0. This is the first time that a computer program has defeated a human professional player in the full-sized game of Go, a feat previously thought to be at least a decade away.
Lonestar developed by Texas A&M is a possible tool that prospectors can utilize to locate mining opportunities on asteroids.
Astronauts fired this small, rectangular hunk from the International Space Station today. The payload will separate into two autonomous satellites as part of a research program to take us one tiny step closer towards making asteroid mining a reality.
If we ever want to mine asteroids, we’re going to need to step up our game for multiple satellites sharing data and working together. A pair of Texan universities are working together on a four-mission sequence to create a pair of robots that can autonomously rendezvous and dock in space. The project is called Low Earth Orbiting Navigation Experiment for Spacecraft Testing Autonomous Rendezvous and Docking — or Lonestar if you ignore the D.
Researchers at Harvard are working to identify the brain processes that make humans so good at recognising patterns. Their ultimate goals is to develop biologically-inspired computer systems for smarter AI. Computers inspired by the human brain could be used to detect network invasions, read MRI images, and even drive cars.
Their ultimate goals is to develop biologically-inspired computer systems for smarter AI.
This just in: Aipoly Vision* — a free AI app that runs on your iPhone/iPad** (Android coming) and recognizes objects and colors — is now live on the App store, Aipoly Inc. co-founder Alberto Rizzoli just told me in an email.
Of course, I immediately downloaded the app, launched it on my iPhone 6s+, and tested it. It works spectacularly. Its voice names objects or colors in real time as a walk around and also displays objects’ names. I am blown away. Here’s a sample:
Aside from a few minor glitches (the swivel chair was also named “office” and “padded stool” and a banana was also named “bug” and “handle” — but I taught it the right name using its “pencil” tool), Aipoly Vision was astoundingly accurate. Colors were a problem with small objects because of backgrounds, but works OK for most large objects, walls, and floors, the company says.
Overall, this is a good article. However, for AI to truly take off across industry; you must understand the industries that you’re trying to enable. I keep finding this gap in all of the AI discussions.
Yes, we have opportunities in the consumer space; however, if you truly want to be embraced by industry to enable it’s front and back office operations you must ensure that the AI that you’re developing can easily support and enable businesses. Granted not all AI belongs in business and are sometimes better suit for the consumer space or government and vice versa. However, when designing and developing AI; you truly have to know up front who is your primary targeted audience and remain focused towards that audience.
Dr. Kailash Nadh, who holds a PhD in artificial intelligence from London’s Middlesex University and is the CTO of financial technology firm Zerodha, talks about why AI hasn’t picked up yet and what lies in the future.
The burgeoning field of nanotechnology promises an indefinite range of capabilities in medicine, optics, communications, and other facets of applied science and engineering. On that front, the U.S. Defense Advanced Research Projects Agency’s (DARPA) Atoms 2 Products program (A2P) is funding 10 companies, universities, and institutions to develop mass-manufacturing techniques and technologies for functional products made up of nanoscale constituents. The project demonstrates a mere slice of the contributions in the mass movement to make nanotechnology a part of our everyday lives.
The following gallery highlights the work of five DARPA-funded projects in the program. The slides describe an atomic calligraphy technique for 2D atomic printing, a manufacturing method for producing high-frequency “Nanolitz” wires, the construction of pop-up sensors for laparoscopy, and a conjunct effort to use micro-robotics to build the assemblers of nanodevices.
““If you think it’s too early to think about something, it’s probably slightly too late.””
Scalpers offered contact lenses guaranteed to fool any ocular-based biometric ticketing technology.
He was right, of course, which explains all those people arriving at the stadium in all the usual ways. Some came by autonomous cars that dropped them off a mile or more from the stadium, their fitness wearables synced to their car software, both programmed to make their owner walk whenever the day’s calories consumed exceeded the day’s calories burned. Others turned up on the transcontinental Hyperloop, gliding at 760 miles per hour on a cushion of air through a low-pressure pipeline, as if each passenger was an enormous bank slip tucked into a pneumatic tube at a drive-through teller window in 1967. That was the year the first Super Bowl was played, midway through the first season of Star Trek, set in a space-age future that now looks insufficiently imagined.
And so hours before Super Bowl 100 kicked off—we persist in using that phrase, long after the NFL abandoned the actual practice—the pregame scene offered all the Rockwellian tableaux of the timeless tailgate: children running pass patterns on their hoverboards—they still don’t quite hover, dammit—dads printing out the family’s pregame snacks, grandfathers relaxing in lawn chairs with their marijuana pipes.
