Lancaster University is developing artificial intelligence (AI) software for servers that could potentially drive down the amount of energy consumed by datacentres. A collection of our most popular articles on datacentre management, including: Cloud vs. Colocation: Why both make sense for the enterprise right now; AWS at 10: How the cloud giant shook up enterprise IT and Life on the edge: The benefits of using micro datacenters This email address is already registered. By submitting my Email address I confirm that I have read and accepted the Terms of Use and Declaration of Consent. By submitting your personal information, you agree that TechTarget and its partners may contact you regarding relevant content, products and special offers. You also agree that your personal information may be transferred and processed in the United States, and that you have read and agree to the Terms of Use and the Privacy Policy.

While America was looking the other way because #ElectionNight, GoPro revealed its new Karma drones have one little issue: They sometimes stop flying. The company announced Tuesday it was recalling around 2,500 Karma drones. According to a statement emailed to Mashable, a number of the drones lost power during operation. Customers can return the item to its place of purchase for a full refund. "Safety is our top priority, GoPro founder and CEO Nicholas Woodman said. "We are working in close coordination with both the U.S. Consumer Product Safety Commission and Federal Aviation Administration.

Advances in machine learning are making security systems easier to train and more flexible in dealing with changing conditions, but not all use cases are benefitting at the same rate. Machine learning, and artificial intelligence, has been getting a lot of attention lately and there's a lot of justified excitement about the technology. One of the side effects is that pretty much everything is now being relabeled as "machine learning," making the term extremely difficult to pin down. Just as the word "cloud" has come to mean pretty much anything that happens online, so "artificial intelligence" is rapidly moving to the point where almost anything involving a computer is getting that label slapped on it. "There is also a lot of hype," said Anand Rao, innovation lead for US analytics at PricewaterhouseCoopers LLC.

Tokio Marine & Nichido Fire Insurance Co. will extend automobile insurance coverage to accidents involving automated driving cars for all policyholders without costs from April 2017. The core unit of Tokio Marine Holdings Inc. will be the first to give such insurance coverage in Japan, officials said Tuesday. Tokio Marine will attach a special provision to cover self-driving car accidents to all contracts renewed or newly concluded in and after April 2017. The move is aimed at preventing victims of automated driving car accidents from being left without relief for a long time. In Japan, existing car insurance products do not cover self-driving car accidents unless the driver's fault is confirmed. This makes it necessary for accident victims to lodge damages claims against automakers and others on their own.

Machine learning is a buzzword that has picked up steam across several industries, and especially in the cybersecurity space we see more and more companies adding machine learning capabilities as a differentiator into their marketing materials. However, machine learning has been around for decades, and many security companies have been using it under the hood for a while. So what is changing, how much is hype and what shows promise? To better understand the value of machine learning, it's important to take a step back at how most security tools work. The traditional workhorses of cybersecurity have been signatures and heuristics.

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.

Confidence interval is abbreviated as CI. In this new article (part of our series on robust techniques for automated data science) we describe an implementation both in Excel and Perl, and discuss our popular model-free confidence interval technique introduced in our original Analyticbridge article, as part of our (open source) intellectual property sharing. This is part of our series on data science techniques suitable for automation, usable by non-experts. The next one to be detailed (with source code) will be our Hidden Decision Trees. Figure 1 is based on simulated data that does not follow a normal distribution: see section 2 and Figure 2 in this article. Classical CI's are just based on 2 parameters: mean and variance.

Rather than leading to the violent downfall of humankind, artificial intelligence is helping people around the world do their jobs, including doctors who diagnose sepsis in patients and scientists who track endangered animals in the wild, experts said Thursday (Oct. Advancements in the field of artificial intelligence (AI) haven't always been met with enthusiasm. Famed astrophysicist Stephen Hawking warned on several occasions that a fully developed AI could destroy the human race, and Hollywood sci-fi movies are rife with fierce robots battling humans for control. But at yesterday's conference -- attended by the country's leading researchers, innovators, entrepreneurs and students -- scientists explained how newly developed AI is accelerating research and improving lives. Here is a look at five AI inventions that are already redefining technology.

There are many good reasons why traditional security practices are becoming less effective at protecting against cyberattacks. There is too much security-related data flooding the network from an increasing number of users and devices. There is a lack of skilled personnel to watch over and analyze this data. And the security staff you have likely wastes too much time chasing down false positives. Valuable minutes -- or even hours -- can tick by before analysts and incident responders are aware of a threat.

Last month, President Barack Obama sat down with WIRED's Editor-in-Chief and MIT Media Lab director Joi Ito to discuss the government's role in the ongoing artificial intelligence revolution. While President Obama is sure that Washington has a critical part to play -- particularly in regulating AI to protect the American labor force -- it is equally important that its involvement doesn't stymie the development and implementation of the technology, he says. When it comes to regulating AI, the president believes that government involvement should be limited, especially during its earlier stages of research and development. "The way I've been thinking about the regulatory structure as AI emerges is that, early in a technology, a thousand flowers should bloom," Obama tells WIRED. "The government should add a relatively light touch, investing heavily in research and making sure there's a conversation between basic research and applied research."