The U.S. Environmental Protection Agency is revising the Energy Star specification for servers to take into account significant system design changes and help buyers make effective purchasing decisions. Over the last few years, server makers have increasingly used coprocessors to boost computing power and given memory a bigger role in processing data. While memory has gotten more power-efficient, coprocessors can suck up a lot of energy. The upcoming, version 3.0 of the Energy Star spec for servers is aimed at helping buyers understand the power-efficiency levels of the new systems. The Energy Star program is already used in computers, appliances, electronics and many other products.

Maybe Skynet will not be our future. Maybe artificial intelligence will not be the machines that disdainfully wipe us out, but instead, will be the long-awaited "little child" who finally leads our species out of its vicious cycles of violence, red in tooth and claw. I had an interesting thought while - appropriately - sitting on a beach by Malibu watching the red sun sink into the sea... Humans evolved as prey animals. According to Sapiens author, Yuval Harari, for a whoppingly overwhelming majority of our evolution, we were bear and tiger food. And so we developed the quick-twitch fight-or flight reactivity of prey animals, always on guard.

Many years ago, I discovered the Mac's built-in computer voice that would say anything you wanted with a few keystrokes on the command line. Of course, I immediately tested the feature by making my computer swear. Getting a computer to say things it shouldn't is practically a tradition. That's why it came as no surprise when Tay, the millennial chatbot created by Microsoft, started spewing bigoted and white supremacist comments within hours of its release. Tay began as an experiment in artificial intelligence released by Microsoft on Wednesday.

Machine learning is generating a tremendous amount of attention these days from the press as well as the practitioners. And rightly so – machine learning is a transformative technology. But despite the references to the topic, the money raised from venture capitalists, and the spotlight that Google is bringing to the subject, machine learning is still poorly understood outside of a core group of highly technical leaders. This has the effect of underestimating how transformative machine learning is going to be. It also has the effect of shielding business leaders from what they need to do to prepare for the era of machine learning.

We have seen incredible progress in machine learning and artificial intelligence (AI) over the past few years, especially through the application of deep learning algorithms. AI systems will get even better as more data is collected, so faster data gathering and better data integration should lead to smarter and more useful AI systems. Recently I described a new class of system that I believe will take form and leverage AI and combine workflow automation to improve how care is delivered -- I termed this: "Intelligent Clinical Decision Automation." This AI-powered automation will consume vast amounts of data and will automate entire processes or workflows, learning and adapting as it goes. Some clinicians and others may be concerned that this sort of automation removes the "gut instinct" of the experienced professional from the mix, but in fact it is that sort of thinking and reasoning process -- even unconscious reasoning process -- that is embodied in this approach.

There are very few data sets telling us what we need to know,

It took less than 24 hours for Twitter to corrupt an innocent AI chatbot. Yesterday, Microsoft unveiled Tay -- a Twitter bot that the company described as an experiment in "conversational understanding." The more you chat with Tay, said Microsoft, the smarter it gets, learning to engage people through "casual and playful conversation." Pretty soon after Tay launched, people starting tweeting the bot with all sorts of misogynistic, racist, and Donald Trumpist remarks. And Tay -- being essentially a robot parrot with an internet connection -- started repeating these sentiments back to users, proving correct that old programming adage: flaming garbage pile in, flaming garbage pile out.

I use the Amazon website nearly every day in Japanese; the company probably has a pretty good idea by now of who I am and what I'm into. Last month I even used an Amazon service that offers expert wine advice over the phone, which is quite understandably not available in English. But if the Echo came out here, I would likely have two choices at best: use it in English and miss out on the deepest integration with Amazon's fast-growing ecosystem -- I wouldn't be able to ask about most Japanese products or services in English, for example -- or use it in my second language and miss out on the ability to interact with Alexa as naturally as possible. Granted, the Echo sounds cool enough that I'd still probably buy one even if I could only use it in Japanese. But its functionality is one-way and focused on the home; it's not a mobile communications device.

Robotics and Autonomous Systems (RAS) is one of the'Eight Great Technologies' identified by the UK Government in 2012. A national strategy for RAS innovation from a'RAS Special Interest Group' was published by Innovate UK in 2014. The Government responded to that strategy in March 2015 (PDF 405 KB) and agreed to establish a RAS Leadership Council to oversee its execution. The Special Interest Group also published'The UK Landscape for Robotics and Autonomous Systems' in 2015. The Engineering and Physical Sciences Research Council launched an UK-RAS network, also in 2015.

You are free to share this article under the Attribution 4.0 International license. One of the biggest challenges in fighting poverty is the lack of reliable information. In order to aid the poor, agencies need to map the dimensions of distressed areas and identify the absence or presence of infrastructure and services. But in many of the poorest areas of the world such information is rare. "There are very few data sets telling us what we need to know," says Marshall Burke, an assistant professor of Earth system science at Stanford University.