https://youtube.com/watch?v=ZN2ZiyVffPI
1st success seen in system designed to help aircraft automatically avoid mid-air collisions.
Flight tests demonstrate optical sense-and-avoid capability that detects and tracks nearby aircraft, setting the stage for future manned and unmanned aircraft to autonomously steer clear of them.
Very nice; we’re getting closer.
But superposition is fragile, and finding ways to preserve it is one of the chief obstacles to developing large, general-purpose quantum computers. In today’s Nature, MIT researchers describe a new approach to preserving superposition in a class of quantum devices built from synthetic diamonds. The work could ultimately prove an important step toward reliable quantum computers.
In most engineering fields, the best way to maintain the stability of a physical system is feedback control. You make a measurement — the current trajectory of an airplane, or the temperature of an engine — and on that basis produce a control signal that nudges the system back toward its desired state.
The problem with using this technique to stabilize a quantum system is that measurement destroys superposition. So quantum-computing researchers have traditionally had to do without feedback.
Could we see race car driver careers become all AI? Nvidia is testing the concept.
Formula E is going completely autonomous with the all-new Roborace series slated for the upcoming race season. At its GTC developer conference, Nvidia announced these autonomous, electric race cars will be powered by Nvidia Drive PX 2, a supercomputer built for self-driving cars.
Drive PX 2 is powered by 12 CPU cores and four Pascal GPUs that provides eight teraflops of computer power. The supercomputer-in-a-box is vital to deep learning and trains artificial intelligence to adapts to different driving conditions, including asphalt, rain and dirt.
At a time when PCs have become rather boring and the market has stagnated, the Graphics Processing Unit (GPU) has become more interesting and not for what it has traditionally done (graphical user interface), but for what it can do going forward. GPUs are a key enabler for the PC and workstation market, both for enthusiast seeking to increase graphics performance for games and developers and designers looking to create realistic new videos and images. However, the traditional PC market has been in decline for several years as consumer shift to mobile computing solutions like smartphones. At the same time, the industry has been working to expand the use of GPUs as a computing accelerator because of the massive parallel compute capabilities, often providing the horsepower for top supercomputers. NVIDIA has been a pioneer in this GPU compute market with its CUDA platform, enabling leading researchers to perform leading edge research and continue to develop new uses for GPU acceleration.
Now, the industry is looking to leverage over 40 years of GPU history and innovation to create more advanced computer intelligence. Through the use of sensors, increased connectivity, and new learning technique, researchers can enable artificial intelligence (AI) applications for everything from autonomous vehicles to scientific research. This, however, requires unprecedented levels of computing power, something the NVIDIA is driven to provide. At the GPU Technology Conference (GTC) in San Jose, California, NVIDIA just announced a new GPU platform that takes computing to the extreme. NVIDIA introduced the Telsa P100 platform. NVIDIA CEO Jen-Hsun Huang described the Tesla P100 as the first GPU designed for hyperscale datacenter applications. It features NVIDIA’s new Pascal GPU architecture, the latest memory and semiconductor process, and packaging technology – all to create the densest compute platform to date.
Reports of the death of car-buying among millennials turn out to have been greatly exaggerated. But there’s one big reason ride-hailing services like Uber, and eventually autonomous vehicles, are still a threat to private car ownership.
Put simply, we just don’t use our cars very much.
Ask a member of Facebook’s growth team what feature played the biggest role in getting the company to a billion daily users, and they’ll likely tell you it was photos. The endless stream of pictures, which users have been able to upload since 2005, a year after Facebook’s launch, makes the social network irresistible to a global audience. It’s difficult to imagine Facebook without photos. Yet for millions of blind and visually impaired people, that’s been the reality for over a decade.
Not anymore. Today Facebook will begin automatically describing the content of photos to blind and visually impaired users. Called “automatic alternative text,” the feature was created by Facebook’s 5-year-old accessibility team. Led by Jeff Wieland, a former user researcher in Facebook’s product group, the team previously built closed captioning for videos and implemented an option to increase the default font size on Facebook for iOS, a feature 10 percent of Facebook users take advantage of.
Automatic alt text, which is coming to iOS today and later to Android and the web, recognizes objects in photos using machine learning. Machine learning helps to build artificial intelligences by using algorithms to make predictions. If you show a piece of software enough pictures of a dog, for example, in time it will be able to identify a dog in a photograph. Automatic alt text identifies things in Facebook photos, then uses the iPhone’s VoiceOver feature to read descriptions of the photos out loud to users. While still in its early stages, the technology can reliably identify concepts in categories including transportation (“car,” “boat,” “airplane”), nature (“snow,” “ocean,” “sunset”), sports (“basketball court”), and food (“sushi”). The technology can also describe people (“baby,” “smiling,” beard”), and identify a selfie.
Three days ago, when Global Equities Research projected more than 300,000 reservations for the Tesla Model 3 electric car by the start of this week, that number seemed outlandish.
And yet, by the end of Saturday, the global total had reached 276,000, according to a tweet by Tesla CEO Elon Musk.
When the Model 3 was first unveiled in California on Thursday evening, the number of deposits that day alone had already crossed 100,000.
