Computers are better than most humans at playing chess. I'm assuming here…I've not yet had sex with a robot, unless you consider my ex-girlfriend. Then, yeah, I've had sex with one. That's 19-year-old world champion Ke Jie upon a recently losing a game of Go to Google's AlphaGo robot. Source: "I believe the future belongs to AI"

Monkey brains have sections dedicated solely to social interactions, a new finding that researchers say could help us better understand the human mind. Scientists scanning the brains of rhesus macaques found that certain parts were active when the monkeys watched videos of social interactions between other monkeys, but that same network was largely inactive in response to other images. A study in the journal Science said those brain regions that were purely analyzing social interactions are in the same places as the ones in the human brain that are associated with similar processes, like the ones that help us understand other people's intentions and what they are thinking, which is called the theory of mind. As the scientists were showing the monkeys the social videos and scanning their brains, they also followed the monkey's gaze to see where the primates were looking (tracked by a red dot in the gif below). The results were "both unexpected and mind-boggling," researcher Winrich Freiwald said in a statement from Rockefeller University, referring in part to the concept that a brain network would power down when, in the words of the university, it is "denied its preferred input."

For decades, technology has relentlessly made phones, laptops, apps and entire industries cheaper and better--while health care has stubbornly loitered in an alternate universe where tech makes everything more expensive and more complex. Now startups are applying artificial intelligence (AI), floods of data and automation in ways that promise to dramatically drive down the costs of health care while increasing effectiveness. If this profound trend plays out, within five to 10 years, Congress won't have to fight about the exploding costs of Medicaid and insurance. Instead, it might battle over what to do with a massive windfall. Today's debate over the repeal of Obamacare would come to seem as backward as a discussion about the merits of leeching. One proof point is in the maelstrom of activity around diabetes, the most expensive disease in the world.

AI and Machine Learning was voted the most transformative analytics tool for insurance. In fact, 94% of respondents agreed that AI is going to have a medium or significant impact on analytics. AI is going to hit insurance big time – so you need to ensure you're prepared for the future. One way to do this is to check out our newly released "AI, Analytics and GDPR Survey 2017", where we quizzed 250 of the brightest minds in insurance. By reading it, you'll get the low-down on the latest trends in analytics, AI and GDPR and be able to adjust your strategy accordingly.

Children and adults alike share an often unconscious need to fiddle and fidget, and the market for toys and gadgets to tackle these temptations seems to have exploded in recent years. But the science behind exactly what causes our drive to distraction remains unclear. In an article with The Conversation, Harriet Dempsey-Jones, a postdoctoral researcher in clinical neurosciences from the University of Oxford, suggests some possible explanations. And she also warns that using these types of toys may give off the wrong impression to people we might be talking to while playing with them. The growing craze for fidget spinners (pictured), marketed as stress relievers, has led to them being banned in some schools.

The desire for users to complete everyday tasks and functions using AI is high. But current AI solutions often fall short of expectations due to limitations in capability and functionality. "Effective learning is critical to creating a compelling experience in this way," commented Christopher Dodge, Associate Director and report author. "Many AI solutions require too much upfront action from the user; manually inputting data or linking profiles from different apps to ensure inclusion in one service is time-consuming and clumsy." Correctly identifying an individual within one ecosystem also impacts basic tasks, especially if the solution cannot identify the individual requesting the action.

Robots have already cost millions of factory jobs across the nation. Next up could be jobs at your local stores. Between 6 million to 7.5 million existing jobs are at risk of being replaced over the course of the next 10 years by some form of automation, according to a new study this week from by financial services firm Cornerstone Capital Group. That represents at least 38% of the current retail work force, which consists of 16 million workers. Retail could actually lose a greater proportion of jobs to automation than manufacturing has, according to the study.

Founded in 2010, RAVN has developed an AI platform that can organize, discover and summarize relevant information from large volumes of documents and unstructured data. Businesses are using RAVN's unique technology to analyze legal documents like contracts and leases, identify information which is privileged or subject to compliance and automate document classification for easier search and governance. "We have been using RAVN over the past seven months to analyze global supplier agreements," said Horia Selegean, Head of Revenue & Margin Assurance, BT. "We anticipate cost savings of tens of millions of pounds every year through discovering contract optimizations and synergies." The Serious Fraud Office, a UK-governmental department in charge of prosecuting complex cases of fraud and corruption, recently used RAVN to help a team of investigators sift through 30 million documents. RAVN processed 600,000 documents per day -- a target that would be nearly impossible for a human work staff -- allowing investigators to save many months of work.

On May 11, 1997, a computer showed that it could outclass a human in that most human of pursuits: playing a game. The human was World Chess Champion Garry Kasparov, and the computer was IBM's Deep Blue, which had begun life at Carnegie Mellon University as a system called ChipTest. One of Deep Blue's creators, Murray Campbell, talked to the IDG News Service about the other things computers have learned to do as well as, or better than, humans, and what that means for our future. What follows is an edited version of that conversation. IDGNS: Is it true that you and Deep Blue joined IBM at the same time?

Garry Kasparov, one of the greatest chess players of all time, is famous for his pair of faceoffs against the IBM supercomputer Deep Blue. Kasparov won the first match against the computer, 4-2, in 1996, but lost in the rematch, 3½-2½, in 1997. He recently published a book, "Deep Thinking," about the experience. Business Insider recently spoke with Kasparov about Deep Blue, his thoughts on AI, and machine advancements over the past 20 years -- and how he sees the interplay between machine intelligence and humanity. This interview has been edited for clarity and length. Garry Kasparov: AI as a concept is surrounded by mythology. Most of the things we mention we understand. You know, if we say "white," we all see it's white. If we talk about elements of computer science or some general items, we are in agreement.