US Government report lays out guidance for AI use and regulation and puts regulating super AI's in the too hard bucket Artificial Intelligence (AI) research and development is starting to reach critical mass and new breakthroughs are being announced almost every day. Now a new report from the US Office of Science Technology Policy (OSTP), who advises Barak Obama directly on AI matters has prepared a new report on the technology which they see is increasingly poised to reshape the way we live and work. Titled Preparing for the Future of Artificial Intelligence the report makes 23 policy recommendations on a number of topics concerned with the best way to harness the power of machine learning and algorithm driven intelligence for the benefit of society. The OSTP position is that government has several roles to play in driving the direction of AI. Namely, "It should convene conversations about important issues and help to set the agenda for public debate. It should monitor the safety and fairness of applications as they develop, and adapt regulatory frameworks to encourage innovation while protecting the public. It should support basic research and the application of AI to public goods, as well as the development of a skilled, diverse workforce. And government should use AI itself, to serve the public faster, more effectively, and at lower cost."

When we talk about artificial intelligence (AI) most people still imagine robots who can talk, act, and behave (to a certain extent) like a human being -- like a C-3PO (Star Wars), sans the metallic look. Or maybe, a supercomputer that can read human behavior so well that it interacts seamlessly with us, while controlling the system -- like Hal 9000 (2001: A Space Odyssey) or Auto (Wall-E). While, arguably, we may not be there yet in terms of our command of AI, we are not that far. AI is definitely the direction tech development is taking, as evidenced by most recent trends, including the formation of a partnership by tech giants to push the frontier of AI. While we may not be nearing the Singularity, AI has taken leaps and bounds of improvement over the past few years alone.

Artificial intelligence (AI) is becoming more and more prevalent in almost every facet of people's day-to-day lives, from its ability to defeat world-class chess players to its implementation into self-driving cars. AI is hot, flashy, buzzworthy and is the future of many industries and applications, but many consumers don't realize the subtle way it is already influencing and shaping the world of retail. Thanks to an abundance of consumer data at their fingertips, retailers have slowly and subtly begun rolling out applications for many sectors of the retail industry, everything from using AI to offer better product recommendations, to chatbots that can carry on an (almost) lifelike conversation with consumers and help push them toward checkout, to being utilized in image recognition systems. "The pertinent question isn't necessarily when but where you'll see AI deployed. And the truth of the matter is that AI can benefit essentially every step and process of eCommerce, from site layout to personalization to -- and this part is extremely important -- customer happiness," Andy Narayanan, vice president of visual intelligence at Sentient, an artificial intelligence software provider, wrote for Total Retail in a piece back in July.

Facebook founder Mark Zuckerberg has received an offer from a famous face for his personal artificial-intelligence assistant: Robert Downey Jr. Mr. Zuckerberg turned to fans on Thursday for suggestions on who might provide the voice work for his AI and soon heard from Marvel's "Iron Man." The famous actor, whose character Tony Stark interacts with a computer named Jarvis, said he would be happy to oblige -- for charity. "I'll do in a heartbeat if Bettany gets paid and donates it to a cause of Cumberbatch's choosing…that's the right kind of STRANGE!" Mr. Downey Jr. said on the CEO's Facebook page.

DeepMind, an artificial intelligence firm that was acquired by Google in 2014 and is now under the Alphabet umbrella, has developed a computer than can refer to its own memory to learn facts and use that knowledge to answer questions. DeepMind says its new AI model, called a differentiable neural computer (DNC), can be fed with things like a family tree and a map of the London Underground network, and can answer complex questions about the relationships between items in those data structures. For example, you could get responses to questions like, "Starting at Bond street, and taking the Central line in a direction one stop, the Circle line in a direction for four stops, and the Jubilee line in a direction for two stops, at what stop do you wind up?" It's these networks that helped DeepMind's AlphaGo AI defeat world champions at the complex game of Go.

As technologist Joi Ito, director of the MIT Media Lab and a board member at the The New York Times and at Sony, recently predicted, "This is the year artificial intelligence becomes more than just a computer science problem." This week, the White House issued a formal position paper with 23 recommendations on artificial intelligence. Let me cut to the chase: they don't think superhuman A.I. is imminent. While you're relaxing in the good news, take in the pleasant surprise that the National Science and Technology Council (NSTC) and the Office of Science and Technology Policy (OSTP), which advises the President in policy and budget development, coordinated efforts to deliver this cohesive position paper. The outcome is a chunky, committee-clarified read, but for all that, it cuts to the chase on big issues in nontechnical language.

First there was analytics; then there was cognitive computing. Put them in a blender and the result is something completely new: cognitive analytics. "We see cognitive analytics as the way in which the human brain approaches a problem," says Stuart Gillen, director of business development at SparkCognition Inc., an Austin, Texas, company that creates products powered by artificial intelligence to enhance cybersecurity and leverages machine learning technology to predict equipment failures before they happen. "Rather than being focused on one particular technique, where we see a lot of artificial intelligence organizations going, we use a variety of different patterns and learn from them." Developers within corporate IT will play a key role in integrating cognitive analytics services with existing data stores and incoming data streams.

Artificial-intelligence (AI) systems known as neural networks can recognize images, translate languages and even master the ancient game of Go. But their limited ability to represent complex relationships between data or variables has prevented them from conquering tasks that require logic and reasoning. In a paper published in Nature on October 12, the Google-owned company DeepMind in London reveals that it has taken a step towards overcoming this hurdle by creating a neural network with an external memory. The combination allows the neural network not only to learn, but to use memory to store and recall facts to make inferences like a conventional algorithm. This in turn enables it to tackle problems such as navigating the London Underground without any prior knowledge and solving logic puzzles.

Google is planning to release its own smartwatch to take on the Apple Watch soon, according to leaks. The company will make two of its own watches, according to new leaks. They're expected to be released at the beginning of 2017. The leak follows Google's launch of the Pixel and Pixel XL phones. Those are the first that Google made itself – and as such bake in an artificially intelligent assistant that isn't available to any other Android users.

The internet bookmark aspires to be the digital equivalent of the sticky note you paste on an important page in a college textbook. But that's where the metaphor falls apart. If the internet is a college textbook, it's an infinitely dense one, where every chapter covers a different subject, and someone has stuck a sticky note on every page. The problem that nearly every bookmarking site inevitably needs to solve is one of organization. Pinterest does this with boards; other bookmarking services, like Pinboard, do so with tags.