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. That's huge, because it means that future AI could respond to queries from humans without being taught every possible correct answer. 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?" DeepMind says its DNC could also help you plan an efficient route from Moorgate to Piccadilly Circus. Similarly, it could understand and answer questions about the relationships between people from a large family, like, ""Who is Freya's maternal great uncle?" This discovery builds on the concept of neural networks, which mimic the way the human mind works.

Computational workloads are growing, and processors, memory, and storage are getting faster at a blazing pace. Emerging technologies could leave computers choking for bandwidth. The potential chokepoint worries companies like Google, IBM, Samsung, and Dell, which are moving to remedy the problem. New specifications from two new consortia will bring data unprecedented boosts in data transfer speeds to computers as early as next year. OpenCAPI Consortium's connector specification will bring significant bandwidth improvements inside computers.

Having stepped down from the industry after 40 years to become warden of his alma mater, New College, Oxford, Ogilvy & Mather's former global chairman and chief executive reminisces about the'bad men' years, ruminates on today's challenges and proposes how adland can regain its swagger.

General Electric (GE), the largest industrial company in the US, says it has developed processes that more than double the speed of innovation and which have the potential to completely restructure its own business. GE will next week launch its first business venture, called Fuse, that will test a hugely ambitious and radical approach to creating new companies through processes and technologies designed to harness the work of global crowds of experts. Dyan Finkhousen is Director of GE's Open Innovation and Advanced Manufacturing group. The GE startup "will usher in what we believe is the future of work," said Dyan Finkhousen, Director of GE's Open Innovation and Advanced Manufacturing group. See also: Emerging technologies to power your systems of insight Obama's report on the future of artificial intelligence: The main takeaways Robot security: Making sure machines don't become the latest big threat She was speaking at Brightidea's Synthesize user conference in San Francisco.

Osram recently spun off its lamps division, branding it Ledvance. But little seems to have changed when it comes to the Lightify LED bulb product line, which has a diversity that looks a lot like it did last year. The one big twist: The company has added a full-color tunable bulb to its lineup to complement the white-only bulb we reviewed last year. Firmware updates have also taught older products a few new tricks. Ledvance Lightify bulbs are built to closely mimic standard incandescents in appearance, and they're designed to work with the Lightify Gateway. The gateway is a small ZigBee device that plugs into any wall socket near where you have the bulbs installed, easily bridging the gap between lighting and your smartphone.

Designed to help understand the fundamentals of DS & Algorithms really well. A must have for programming interviews.

With cloud-based, self-learning search, all the required components are hosted and managed by the vendor, such as Coveo. Because of its scalability, it has the potential to change the customer service industry the same way machine learning has impacted e-commerce and social networks. In the past, the high cost of using and managing machine learning systems meant that machine learning was rarely used for traditional enterprise search or self-service support sites. The cloud makes that affordable to all customers and to all departments, especially when deploying self-learning search on self-service support sites and on communities, because of its ability to scale and handle large volumes of data.

SAN JOSE, CA--(Marketwired - Oct 14, 2016) - Technology leaders AMD, Dell EMC, Google, Hewlett Packard Enterprise, IBM, Mellanox Technologies, Micron, NVIDIA and Xilinx today announced a new, open specification that can increase datacenter server performance by up to 10x, enabling corporate and cloud data centers to speed up big data, machine learning, analytics, and other emerging workloads. Servers and related products based on the new standard are expected in the second half of 2017. The new standard, called OpenCAPI and released today by the newly formed OpenCAPI Consortium, provides an open, high-speed pathway for different types of technology -- advanced memory, accelerators, networking and storage -- to more tightly integrate their functions within servers. This data-centric approach to server design, which puts the compute power closer to the data, removes inefficiencies in traditional system architectures to help eliminate system bottlenecks and can significantly improve server performance. OpenCAPI sets a new standard for the industry, providing a high bandwidth, low latency open interface design specification built to minimize the complexity of high-performance accelerator design.

Products using artificial intelligence (AI) are creeping into our lives: in the home, online, at work, in the marketplace, in the doctor's office. What if AI gets carried away, if it hasn't already? Plenty of movies and books that contemplate this. While those scenarios may be easy to dismiss, the consequences of what could happen are not. Unless it's fully grasped for its benefits, companies that use AI are putting their brands at risk if society doesn't adequately understand how it benefits from the technology.

A new report from the Office of Science Technology Policy (OSTP) addresses the fast-growing field of artificial intelligence (AI), which 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."