Manufacturers often have to deal with up to 800 hours of downtime annually. On average an automotive manufacturer's TDC is 22,000 per minute; that is 1.3M per month! With the advance of predictive analytics, TDC can easily be reduced however only 14% of the manufacturing industry is taking advantage of its big data, according to a recent survey from MESA. Predictive maintenance is realized through the application of sophisticated machine learning techniques to equipment condition data collected in real-time or near real-time. It is now the new standard for reducing cost, risk and lost production in manufacturing facilities.

Getting stitched up by Dr. Robot may one day be reality: Scientists have created a robotic system that did just that in living animals without a real doctor pulling the strings. Much like engineers are designing self-driving cars, Wednesday's research is part of a move toward autonomous surgical robots, removing the surgeon's hands from certain tasks that a machine might perform all by itself. No, doctors wouldn't leave the bedside -- they're supposed to supervise, plus they'd handle the rest of the surgery. Nor is the device ready for operating rooms. But in small tests using pigs, the robotic arm performed at least as well, and in some cases a bit better, as some competing surgeons in stitching together intestinal tissue, researchers reported in the journal Science Translational Medicine.

"The legal industry is ripe for innovation," says attorney and journalist Robert Ambrogi, who covers the role of technology in law. In an influential April 13 blog post, Ambrogi proclaimed a boom in legal tech startups based on a more than doubling of listings on startup directory AngelList. Ambrogi has since produced his own streamlined listing that currently has nearly 500 companies offering technologies to the legal industry. Several are courting attorneys who need better, cheaper ways to sort through the avalanche of legal filings, rulings, and spiderwebs of citations between cases, from the local to federal level. The innovation upsurge may in part be generational.

Facebook chief and co-founder Mark Zuckerberg at the social network's annual developers gathering unveils the option of building chatbots that let software have one-on-one natural language exchanges with people in San Francisco on April 12, 2016. They're all the rage: Kik has them, Facebook wants them, and it seems like every computer coder wants to make them. And why is every company suddenly hot on this new A.I. trend?

Bots have been making the news more and more lately, partly due to the underlying technology becoming more common, and partly due to bots becoming rampaging racists. PCWorld recently suggested that 2016 may be "the year of the bots." But if you read the article, all the examples are of chatbots--bots, to be sure, but only a subset. A bot--to use the broadest sense--is merely "an agent that does an automated process," said Alexis Lloyd, who creates bots and other cutting edge projects at the New York Times Research & Development Lab. But if a "bot" is simply a computer program with an automated function, doesn't that make everything from TweetDeck to your spam filter a bot? "That's where it gets fuzzy," Lloyd said.

Machine learning is at the top of the "hype curve" for emerging technologies and is one of the top 10 strategic technology trends for 2016 according to Gartner. A method of data analysis that automates analytical model building, machine learning can benefit almost any business that gathers data with the intention of acting upon it. It's safe to say that most of us are already interacting with machine learning applications on a daily basis, whether it's Apple's Siri, Facebook's face detection, Amazon and Netflix personalized recommendations, or iOS's autocorrect. What can we learn from this growing trend? What can we do with such a widely applicable technology and how can we maximize its potential?

Researchers tout the potentials of artificial intelligence as a game changer in a range of industries but AI appears to have application in the world of gambling as well. You may not have thought about using artificial intelligence for your Kentucky Derby bets but those who did have turned their 20 to 11,000. The artificial intelligence called UNO, which has earlier predicted the winners of the Super Bowl and the Oscars, appears to have conquered the holy grail of gambling with its successful prediction of the winners in the last weekend's Kentucky Derby. The odds for predicting the top four horses in the right order is 540 to one but this was made possible with UNO's swarm intelligence, which aims to amplify instead of replace human intelligence. The idea is that large groups are better at predicting the outcome of an event compared with any one person.

Bob Greifeld works in an industry where fractions of a second matter. Still, that hasn't stopped the longtime CEO of Nasdaq from taking a workman-like approach to his job. Dan DeFrancesco talks to Greifeld about his journey to Nasdaq, and what he's learned along the way. Bob Greifeld fits the traditional profile of a capital markets CEO. He's well spoken, intelligent and quick-witted.

And pretty soon, they'll come for us. That seems to be the story today, whether from Hollywood or in breathless articles in popular tech magazines about artificial intelligence and nanotechnology. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May. In a world where machines can learn, once humans push the "on" button, there's no stopping our robot overlords, right? When machines become more intelligent, humans are freed to become more creative.

Technology is the future of retail. Digital data, machine learning, cloud-powered analytics and the Internet of Things (IoT) will separate the wheat from the chaff in tomorrow's retail industry.