Digital data and cloud storage follow Moore's law: the world's data doubles every two years, while the cost of storing that data declines at roughly the same rate. This abundance of data enables more features, and better machine learning models to be created. "In the world of intelligent applications, data will be king, and the services that can generate the highest-quality data will have an unfair advantage from their data flywheel -- more data leading to better models, leading to a better user experience, leading to more users, leading to more data," Somasegar says. For instance, Tesla has collected 780 million miles of driving data, and they're adding another million every 10 hours. This data is feed into Autopilot, their assisted driving program that uses ultrasonic sensors, radar, and cameras to steer, change lanes, and avoid collisions with little human interaction.

Sieving through resumes for a job seemed to be a universal problem for small and big companies alike. Gifted with technology, we now have access to many online job portals across the world claiming to find the right job for the right person. But how accurate is this service? It is from here that an idea originated in the brains of Arjun Pratap, founder and CEO of EdGE Networks. He believed that most people are in pursuit of passion, money and status and this, they find hard to capture as a package.

Brace yourselves: Artificial intelligence, virtual reality and a host of new emerging technologies are becoming mainstream. Fortunately, for the federal government, two new digital communities will coalesce around these burgeoning technologies in an effort to promote interagency collaboration, partnerships with industry and to exchange ideas about what works. Launched last month, the Artificial Intelligence for Citizens Services and Virtual/Augmented Reality communities add two new focus areas to General Services Administration's Digital Communities effort, which already boasts some 10,000 members and 16 active mission areas. Justin Herman, digital communities and open government lead at GSA, said the communities arose from direct conversations, feedback and analysis from federal agencies themselves. "Agencies had the need for more information and clarification for how to approach these technologies of tomorrow," Herman told Nextgov.

Firmly rooted in the realm of science fiction, artificial intelligence (AI) has often felt external – something happening out there. In reality, AI is a huge part of our everyday lives. We just don't recognize it. Bank alerts of suspected fraudulent charges, smartphone notifications to exercise, Siri or Cortana's ability to recognize voices – are all examples of AI. "Artificial intelligence is basically where machines make sense, learn, interface with the external world, without human beings having to specifically program it," said Nidhi Chappell, director of machine learning at Intel. AI improves lives in many other areas too. By measuring biometrics in sports, data can help measure how an athlete's playing time impacts injury likelihood.

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Google, Amazon, and Facebook can magically recognize images and voices, thanks to superfast servers equipped with GPUs in their mega data centers. But not all companies can afford that level of resources for deep learning, so they turn to cloud services, where servers in remote data centers do the heavy lifting. Microsoft has made such cloud services trendy with Azure and is one of the few companies offering remote servers with GPUs, which excel in machine-learning tasks. But Azure uses older Nvidia GPUs, and it now has competition from Nimbix, which offers a cloud service with faster GPUs based on the Nvidia's latest Pascal architecture. After renting time on the cloud service, customers get a virtual machine with access to bare-metal server hardware.

Google cut power usage in its data centers by several percentage points earlier this year by trusting artificially intelligent software derived from 1980s-era Atari video games. And in the years to come, the Internet giant not only could save much more electricity, but also solve far larger problems by taking on a much more complex video game. Research scientists at Google's DeepMind unit announced Friday they are developing a computer program that reads data about Blizzard Entertainment's "StarCraft II" games and learns how to play on its own. The software would have to figure out how to split its attention between micromanagement and long-term strategic decisions. It's that maneuvering that could deliver big breakthroughs.

Elon Musk's "Alien Dreadnought" is bringing a German crew on board. Tesla, the electric car company based in Palo Alto, announced Tuesday that it will buy Grohmann Engineering, based in Prum, Germany, to be renamed Tesla Grohmann Automation. Grohmann, founded by Chief Executive Klaus Grohman, is a highly regarded supplier of factory automation systems in industries ranging from automobiles to microelectronics. It has outposts around the world, including offices in Charlotte, N.C. and Chandler, Ariz. The German company employs about 700 people.

Pundits are quick to hype AI and machine learning as the future of everything. But, anyone who has been caught screaming at Siri for its lack of understanding of the most basic of queries knows that we have a long, ponderous way to go before "we have arrived." That's why I find Gil Press' summary of the recent O'Reilly AI Conference so helpful and important. Some of the observations are banal ("AI is not going to exterminate us, AI is going to empower us"), but others capture the essence of what makes AI so promising...and beguiling. AI is hard...get over it The first observation ("AI is difficult") seems obvious, yet for all the wrong reasons. The first thing that makes AI and machine learning difficult comes down to trust.

Ecommerce company Etsy today disclosed in a filing that it spent $32.5 million to acquire Blackbird Technologies, a startup that had developed artificial intelligence (AI) software that could be used for various search applications in the context of shopping. "The Company completed this acquisition to improve the quality and relevance of search on Etsy.com," says the SEC filing. Total consideration for the acquisition was approximately $15.0 million, consisting of $8.1 million in cash and 513,304 shares of the Company's common stock with a fair value of $6.9 million on the acquisition date. Additionally, the Company issued 184,230 shares of common stock or restricted stock units ("RSUs") on the acquisition date with a fair value of $2.5 million which are tied to continuous service with the Company as an employee and are being accounted for as post-acquisition stock-based compensation expense over a three-year vesting period. The Company will pay up to an additional $8.8 million in cash and issue up to an additional 460,575 shares of RSUs post-close with a fair value of $6.2 million, both of which are also tied to continuous service with the Company as an employee and are being accounted for as post-acquisition stock-based and other compensation expense over a three-year vesting period.