Hyundai is working on a new connected car it calls a "high-performing computer on wheels" that will tap big data and analytics for proactive service and constant connection. The company will collaborate with leading global IT and networking companies to develop a self-driving "hyperconnected and intelligent car," it announced Tuesday, with a focus on connecting it to other cars, the office, and the home. Four key areas will help the new cars make the most of data. A smart remote maintenance service, for example, will remotely diagnose and fix vehicle issues before they become apparent, Hyundai said. Autonomous-driving capabilities will be another key element, as will what Hyundai calls "smart traffic" features to help reduce congestion and make trips quicker.

The first GTC took place in a set of hotel ballrooms a few blocks away. That's up from 4,000 last year, a growth rate that's tracked pretty steady since the start of the show. The stage is about five feet off the ground. And on the vast screen is an NVIDIA-green moving image that, as it scans looks like a multi-level rendering of the brain's neural network. With some electronics thrown in between. A great many of those here, though, are scientists and analysts of the computational sort -- those who rely on NVIDIA GPUs to help them crunch the rising sea of data that's engulfing us. A lot are associated with universities, close to 200 of them. Virtually every one of the top 100 university comp sci departments are here. There are also hundreds of companies represented--certainly the dozens of major web-services companies that use artificial intelligence. But also industrials, oil and gas, retail. Err, less so this time. But folks don't seem to mind.

If all humans have the same brain capacity--about 300 million pattern recognizers in our cortices--then what made Albert Einstein special? In his quest to replicate the human brain, renowned AI engineer Ray Kurzweil finds that a big part is: The courage to stick to your convictions. The average human is inherently conventional, reluctant to pursue ideas outside of the norm. "[Courage] is in the neocortex, and people who fill up too much of their neocortex with concern about the approval of their peers are probably not going be the next Einstein or Steve Jobs." – Ray Kurzweil told Wired. If your work elicits ridicule from the rest of the world, pushing past this skepticism could be a strong indication of brilliance.

As artificial intelligence breakthroughs arrive on a near-monthly basis - see what Google's (NASDAQ:GOOG) (NASDAQ:GOOGL) AlphaGo system recently accomplished - Nvidia (NASDAQ:NVDA) execs have been talking to anyone within earshot about the value of its GPUs for handling AI-related computing tasks. Especially for deep learning, a branch of AI focused on using algorithms to uncover patterns within large volumes of content (e.g. The more data a deep learning system takes in, the smarter it becomes. Today, Nvidia stepped up its AI efforts by launching (at its annual GTC conference) the DGX-1, a deep learning-optimized supercomputer that relies on eight of the company's new Tesla P100 GPUs and is declared to provide the throughput of 250 x86 servers (some might beg to differ with that claim). Nvidia, which already sells plenty of Tesla GPUs for third-party supercomputer and high-performance computing ("HPC") systems, is including a deep learning software suite with the DGX-1.

Data scientists and artificial intelligence (AI) researchers require accuracy, simplicity, and speed for deep learning success. Faster training and iteration ultimately means faster innovation and faster time to market. The NVIDIA DGX-1 is the world's first purpose-built system for deep learning with fully integrated hardware and software that can be deployed quickly and easily. Its revolutionary performance significantly accelerates training time, making the NVIDIA DGX-1 the world's first deep learning supercomputer in a box.

Amazon.com Inc. acquired artificial-intelligence startup Orbeus Inc., according to a person familiar with the matter, part of a broader push by the world's largest Internet retailer into smart software for its cloud-computing and connected-device businesses. The acquisition took place in the fall of 2015, said the person who asked not to be identified because Amazon hasn't announced the deal. An Amazon spokeswoman and representatives at Sunnyvale, California-based Orbeus, including Chief Executive Officer Yi Li, did not respond to requests for comment. An online search shows that the startup's domain name, Orbe.us, is owned by registrant Amazon Hostmaster, part of an Amazon subsidiary called Amazon Technologies Inc. Orbeus developed photo-recognition technology based on a powerful type of AI called neural networks and made this available as a consumer application, as well as a service for other companies and developers called ReKognition. It automatically categorized and identified the contents of photos.

The Amazon Echo is an incredible device, mostly because it lets you use voice commands to do everything from playing music to calling up an Uber to controlling your lights and thermostat. Shrink the Echo in half, cut the power cord and remove the hands-free voice commands and the Amazon Tap is what you get. It's a portable Bluetooth speaker, and it still gets you access to Alexa, Amazon's personal voice assistant whom you can boss around, but it didn't sweep me off my feet the way the Echo did. At 130, the Tap is smack in the range of average portable Bluetooth speakers. With a height of 6.2 inches and diameter of 2.6 inches, the Tap is compact enough to toss into your bag.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

As for who might be buying these computers, NVIDIA is positioning this machine for serious research purposes -- the first machines off of NVIDIA's assembly lines will go to ten universities including MIT, Stamford, NYU and Berkeley. The company is also positioning the DGX-1 as a key component of its new AI Driving machine-learning system called Drive PX, which helps to enable vehicle recognition at 180FPS. The goal of having such a relatively system is to make deploying such massive computing power much easier. "Data scientists and AI researchers today spend far too much time on home-brewed high performance computing solutions," Huang said in a press release. "The DGX-1 is easy to deploy and was created for one purpose: to unlock the powers of superhuman capabilities and apply them to problems that were once unsolvable."

Nvidia on Tuesday outlined its Tesla P100 GPU, designed for accelerating data centers, a supercomputer for artificial intelligence called DGX-1 and efforts in everything from autonomous vehicles to virtual reality simulations. At its GPU Technology Conference, Nvidia said its Tesla P100 GPU will land in servers in the first quarter of 2017. The Tesla platform is being used for high performance computing, which is being adopted more for enterprise analytics workloads. The Tesla P100 improves neural network training performance, has better interconnects to scale and has improvements for big data workloads as well as new artificial intelligence algorithms. The company also updated its software developer kit.