Stare across the gallery of the Tate Britain at a Turner and you bring with you a quiet murmur of experiences – a family holiday, an orgasm, that morning's news. What you see works in co-ordination with echoes. But what does a computer see? What does it think when it looks at a Turner? Recognition, the winner of the Tate's IK Prize 2016 for digital innovation, asks – and answers – some of these questions. Made up of multiple artificial-intelligence technologies, Recognition makes use of object recognition, facial recognition and composition analysis to pull up-to-the-minute photojournalism from Reuters, then trawls through Tate Britain's vast collection to plonk a comparable picture beside it.

A study titled, 'Hundred Year Study on Artificial Intelligence', (A100), being carried out by Stanford University aims to know the impact of artificial intelligence on our daily life. The study carried out by 17 experts started with a report'Artificial Intelligence and Life in 2030' that mentioned as to how advancements like drones and autonomous vehicles would merge with society. The panel that includes members from Google, Facebook, Microsoft and IBM has planned to make changes in the report with updates after every five years. Majorly, it is being considered that self-driving would be the one to usher the technology into mainstream. Report's co-author Peter Stone from the University of Texas at Austin and colleagues said that AI would replace human workers at one go.

Americans have a pressing problem: Nobody is saving money. Consider this: One out of every three people has a grand total of zero dollars saved, and 63 percent of Americans do not have enough money saved to cover an unexpected 500 expense. That s bad enough, but these folks are also going to live a lot longer than prior generations all these people drinking kombucha and eating kale chips aren t saving anywhere near enough to pay for the long, long lives they have ahead of them. So, what should we do? Should we put more pressure on employers to nudge their employees into retirement accounts?

Everything in our online life is indexed. Every idle tweet, status update, or curious search query feeds the Google database. The tech giant recently bought a leading artificial-intelligence research outlet, and it already has a robotics company on its books. So what if Google, or Facebook, or any of the companies we entrust our information to, wanted to use our search histories to create an artificially intelligent robot? Writer and director Alex Garland's new film, Ex Machina, looks at just that.

Data scientists are no longer needed to mine data for business value, and organisations should instead look to machine learning platforms.

As I discussed in my previous blogs, artificial intelligence in the form of cognitive computing, robotic processing automation and other technologies presents insurers with many new opportunities for efficiency and for accelerated growth. The question for insurers is whether to use AI to automate processes or to augment the workforce and make it more creative and effective. Many insurers are adapting AI to automate basic underwriting transactions and renewal processing. AI also provides consistent, low-cost performance in making underwriting eligibility decisions. Insurers are exploring the use of AI to augment the expert workforce in areas including risk management, client and/or prospect discovery, coverage recommendations and fraud detection.

Artificial intelligence (AI) technologies are already proliferating in the enterprise. However, many business leaders don't realize they're leveraging technologies that rely on AI, according to a new study by natural language generation (NLG) specialist Narrative Science. Despite the confusion, adoption is imminent. "AI has been around for a long time," says Stuart Frankel, CEO and co-founder of Narrative Science. "While it is super-hot and very buzzy today, there are still some success stories of AI that we just don't consider AI anymore. We use it every day and we're used to it. I think that's a natural progression. Once that esoteric technology that's sort of hard to explain gets wide adoption, it's no longer AI anymore."

Neuroeconomics use all kinds of research methods and experimentations to understand human behavior in different situations. One of these situations is making decisions under risk and uncertainty, where multiple areas of the brain become involved. Neuroscientific research suggests that we humans are not rational beings. Much of our decision making is driven by emotion. Do we want our emotion to play a part? More and more, technologies like SPIXII are using neuroeconomics findings to help us.

Nairobi, Dec 19 (PTI) The WTO talks entered the fifth day today as a deadlock continued over reducing farm subsidies and on providing protection to poor farmers of developing nations, such as India, in case of import surge. The 10th WTO Ministerial was originally scheduled to end last night but developed and developing countries failed to iron out differences on these issues. "The meeting is still on since last night," sources said, adding that a small group of countries -- India, the US, EU, China and Brazil - are discussing the issues. India has made it clear that it would not compromise the interests of farmers and agri-related sectors. It has also asserted to include the public stockholding issue for food security purposes in the preamble of the Nairobi declaration. It also wants that special safeguard mechanism (SSM) should be delinked from market access.

It is now possible for machines to learn how natural or artificial systems work by simply observing them, without being told what to look for, according to researchers at the University of Sheffield. This could mean advances in the world of technology with machines able to predict, among other things, human behaviour. The discovery takes inspiration from the work of pioneering computer scientist Alan Turing, who proposed a test, which a machine could pass if it behaved indistinguishably from a human. The interrogator has to find out which of the two players is human. If they consistently fail to do so – meaning that they are no more successful than if they had chosen one player at random – the machine has passed the test, and is considered to have human-level intelligence.