Google's secretive artificial intelligence researchers have revealed a computer that they hope will one day be able to program itself. Developers at Google's secretive DeepMind start-up, which it bought for $400 million earlier this year, are attempting to mimic some of the properties of the human brain's short-term working memory. By combining the way ordinary computers work with the way the human brain works, the researchers hope the machine will learn to program itself. I'm sorry Dave, I can't Google that: HAL, the smart computer from Stanley Kubrick's 2001 moved a step closer today as developers at Google's secretive DeepMind start-up revealed they are attempting to mimic some of the properties of the human brain's short-term working memory. Its recent Hummingbird search update was created to make Google'more human' - searches can now understand context, like a human brain, for example.

Google has set up an ethics board to oversee its work in artificial intelligence. The search giant has recently bought several robotics companies, along with Deep Mind, a British firm creating software that tries to help computers think like humans. One of its founders warned artificial intelligence is'number 1 risk for this century,' and believes it could play a part in human extinction. An analyst believes Google is in the best position to create the first ever conscious machine and already has related projects in the place. It recently bought a number of robotics firm, such as Meka pictured, for example. Its most recent Hummingbird search update was created to make Google'more human' - searches can now understand context, like a human brain, for example.

With Intel's acquisition of the deep learning startup Nervana Systems on Monday, the chipmaker is moving further into artificial intelligence, a field that's become a key focus for tech companies in recent years. Intel's purchase of the company comes in the wake of Apple's acquisition of Seattle-based Turi Inc. last week, while Google, Yahoo, Microsoft, Twitter, and Samsung have also made similar deals. Those purchases – large tech firms have bought 31 AI startups since 2011 – according to the research firm CB Insights, also underscore a shift. While AI was once thought of as a sci-fi concept, the technology behind it has come to propel a slew of innovations by hardware and software companies that both attract attention – like self-driving cars – and ones that often go unnoticed, like product recommendations on Amazon. "Intel's acquisition of [Nervana] is an acknowledgment that this area of deep learning, machine learning, artificial intelligence, is really an important part of all companies going forward," says David Schubmehl, an analyst who focuses on the field at the research firm IDC. Intel also purchased Saffron Technologies, which aims to solve complex problems using "cognitive computing," last fall.

The artificial intelligence (AI) engine "can understand with near-human accuracy the textual content of several thousands posts per second, spanning more than 20 languages," Facebook announced in a blog post Wednesday. Facebook's newest AI system will allow it to continue to personalize content for its billion plus users, as well as weed out spam and hate speech. The engine also marks another major milestone in deep-learning technology, as Facebook, Google, and Microsoft invest heavily in teaching machines to think. "Having good machine learning models is a force multiplier for a lot of the stuff they are doing," Bradley Hayes, a postdoctoral associate at MIT and the creator of the satirical AI chatbot @DeepDrumpf, told The Christian Science Monitor last month. For Facebook, the "scalability" Mr. Hayes refers to is enormous.

Debates on the future of artificial intelligence often boil down to questions about whether the technology could help humans -- detecting patterns that could help solve crimes or driving autonomous car, for example -- or become the stuff of dystopian nightmares that have long fueled science fiction. With a $1 billion investment in a non-profit called Open AI, Tesla head Elon Musk and several other prominent tech executives are aiming for the former, while taking a swipe at the latter. The new company will make its patents and research open to the public in a bid to increase transparency about AI's potential rather than focusing on its commercial implications, say its backers -- who include LinkedIn co-founder Reid Hoffman, venture capitalist Peter Thiel, the start-up incubator Y-Combinator, and Amazon Web Services. "Since our research is free from financial obligations, we can better focus on a positive human impact," says the group in a statement. "We believe AI should be an extension of individual human wills and, in the spirit of liberty, as broadly and evenly distributed as possible... It's hard to fathom how much human-level AI could benefit society, and it's equally hard to imagine how much it could damage society if built or used incorrectly."

Satellites are best known for helping smartphones map driving routes or televisions deliver programs. But now, data from some of the thousands of satellites orbiting Earth are helping track things like crop conditions on rural farms, illegal deforestation, and increasingly, poverty in the hard-to-reach places around the globe. As much as that data has the potential to provide invaluable information to humanitarian organizations, watchdog groups, and policymakers, there is too much of it to sift through in order to draw insights that could influence important decisions. A team of researchers from Stanford University, however, says it has developed an efficient way. By creating a deep-learning algorithm that can recognize signs of poverty in satellite images – such as condition of roads – the team sorted through a million images to accurately identify economic conditions in five African countries, reported the scientists in the journal Science on Thursday.

Abstract: Deep learning algorithms have recently appeared that pretrain hidden layers of neural networks in unsupervised ways, leading to state-of-the-art performance on large classification problems. These methods can also pretrain networks used for reinforcement learning. However, this ignores the additional information that exists in a reinforcement learning paradigm via the ongoing sequence of state, action, new state tuples. This paper demonstrates that learning a predictive model of state dynamics can result in a pretrained hidden layer structure that reduces the time needed to solve reinforcement learning problems. After training for 0 minutes: Your browser does not support the video tag.

Since their inception, computers have lived in a world of ones and zeros, doggedly processing if-then and and-or statements through multiple language layers. One fascinating technology being developed for self-driving cars may change all that, giving computers a stronger visual understanding of our world, and could possibly be the first step towards an evolving computer self-consciousness. The technology is called "deep learning," a technique for training a computer based on a neural network program, similar to the pathways found in your brain. While researchers apply deep learning in a variety of scenarios, including speech recognition, it's visual recognition that's the most relevant, and the hottest, field for self-driving cars. To safely navigate our cities and suburbs, self-driving cars need to recognize objects in their immediate environment.

Amit Singh, president of Google for Work, speaks at Web Summit 2015. DUBLIN -- Google doesn't presume to know what you're thinking, but the Internet giant will offer its best guess with a new email feature called "smart reply." Unveiled Tuesday, the smart-reply feature in the Inbox by Gmail app analyzes the text of incoming email and offers three tailored responses that you can ignore or customize. Smart reply should arrive this week in the version of the Inbox app that runs on smartphones and tablets powered by Google's Android software and Apple's rival iOS. It may look simple, but under the covers, the capability requires complex technology called deep learning, a newer incarnation of what researchers for decades have called artificial intelligence.

The government has released a report highlighting some of the benefits and challenges that are likely to come about as a result of advances in artificial intelligence being made by companies like Google, DeepMind, and Facebook. Written by Chief Scientific Adviser Sir Mark Walport and published on Thursday, the report provides an overview of where we're at with AI before going on to highlight how it has the potential to fuel innovation and improve government services. The report -- titled "Artificial intelligence: opportunities and implications for the future of decision making" -- also looks at how government should "manage and mitigate" any negative effects that may be brought about as a result of AI. "It is important to recognise that, alongside the huge benefits that artificial intelligence offers, there are potential ethical issues associated with some uses," Walport writes. "Many experts feel that government has a role to play in managing and mitigating any risks that might arise." Walport also wants to open up the conversation on AI to ensure that scientists in the field gain public trust. "Public trust is a vital condition for artificial intelligence to be used productively," he writes.