Any system where humans interact with technology involves a tradeoff: security versus accessibility. The more secure the system, the more difficult it is to access. This poses a dilemma for any organization facing pressure to embrace anytime, anywhere accessibility, the mobile workplace and real-time interaction with customers and employees--and that describes almost every organization today. Advances in artificial intelligence (AI)--and the millions of data points created by the Internet of Things--are starting to change the nature of this tradeoff, particularly where trust is part of the product or service. As AI systems learn more, they can be trained to suggest next best actions, automate some repetitive tasks and minimize the greatest risk: human error.

Earlier this year, Diligent Robotics introduced a mobile manipulator called Poli, designed to take over non-care related, boring logistical tasks from overworked healthcare professionals who really should be doing better things with their time. Specifically, Diligent wants to automate things like bringing supplies from a central storage area to patient rooms, which sounds like it should be easy, but is actually very difficult. Autonomous mobile manipulation in semi-structured environments is hard at the best of times, and things get even harder in places like hospitals that are full of busy humans rushing around trying to save the lives of other humans. Over the past few months, Diligent has been busy iterating on the design of their robot, and they've made enough changes that it's no longer called Poli. It's a completely new robot, called Moxi.

While digitization has strained the marketing department's traditional methods and measures in recent years, the function is regaining its energy by plugging into a rich and abundant power source: data. Existing enterprise data, as well as information gathered from engaging with consumers, has become a valuable business asset. With the advent of machine learning--a type of algorithm that identifies patterns in data and improves with experience--companies can use data to predict and "learn" to identify consumers who appear likely to become high-value customers. The business restructuring taking place today mirrors the transformation that's underway throughout entire industries, from media to manufacturing, as companies rewire to compete in a digitally drenched environment. "For a long time, none of us would have thought that selling food and beverage over e-commerce would have been such a large business," says Shyam Venugopal, vice president for global media and consumer data strategy at PepsiCo.

A few years ago--the company won't say exactly when--some engineers at Apple began to think the iPhone's camera could be made smarter using newly powerful machine learning algorithms known as neural networks. Before long, they were talking with a lean vice president named Tim Millet. Millet leads a team of chip architects, who got to work. When the iPhone X was unveiled last fall, Apple's camera team had added a slick new portrait mode that can digitally adjust the lighting on subjects' faces, and artfully blur the background. It took advantage of a new module added to the iPhone's main chip called the neural engine, customized to run machine learning code.

According to a 2017 University of Washington report, there are hundreds of millions of smart-home devices in more than 40 million U.S. homes. This number is expected to double by 2021. Amazon Echo, Google Home and other devices that have Alexa and Google Assistant built in, have proven to be some of the world's most promising new technologies. These AI-enabled assistants seem capable of doing everything, from turning on lights to answering simple and even complex questions. "OK Google" and "Alexa" have become common household phrases, as these smart connected speakers always have their microphones on, yet don't respond until their "wake words" are mentioned.

This year that game is undeniably Fortnite Battle Royale, an online free-for-all that every teen in America suddenly seems to be playing. It's not just kids, though–everyone from rapper Drake to Los Angeles Laker Josh Hart is a fan. That groundswell of support has propelled Fortnite from a simple video game into a cultural sensation, with hundreds of millions of fans worldwide who play the game, wear the gear and even learn the characters' victory dances. "Fortnite is another in a long line of games like World of Warcraft or Guitar Hero or Minecraft that is changing everything underfoot," says Mat Piscatella, a video-game industry analyst with research firm NPD Group. Fortnite's big draw is a madcap multiplayer mode that drops up to 100 players on an island in a last-person-standing showdown.

When Mangesh Gururaj's wife left home to pick up their child from math lessons one Sunday earlier this month, she turned on her Tesla Model S and hit "Summon," a self-parking feature that the electric automaker has promoted as a central step toward driverless cars. But as the family's $65,000 sedan reversed itself out of the garage, Gururaj said, the car abruptly struck the garage's side wall, ripping its front end off with a loud crack. The maimed Tesla looked as if it would have kept driving, Gururaj said, if his wife hadn't hit the brakes. No one was hurt, but Gururaj was rattled: The car had failed disastrously, during the simplest of maneuvers, using one of the most basic features from the self-driving technology he and his family had trusted many times at higher speeds. "This is just a crash in the garage. But what if we were summoning and there was a child it didn't see?" said Gururaj, an IT consultant in North Carolina, who bought the car last year.

It may be a long time before you can own a truly self-driving car. But chipmakers are placing bets that you will. On Tuesday, the Japanese chipmaker Renesas, the second-largest provider of semiconductors for the automotive industry, said it will acquire San Jose based chipmaker Integrated Device Technology (IDT) for $6.7 billion, in part to prepare for autonomous vehicles. IDT has not historically provided chips for cars, but it does have sensor and wireless technologies that could help Renesas compete in the market for chips for autonomous vehicles. "Renesas and IDT have complementary technologies," says Objective Analysis analyst Jim Handy.

Insects are quite good at not running into things, and just as good at running into things and surviving, but targeted, accurate precision flight is much more difficult for them. As cute as insects like bees are, there just isn't enough space in their fuzzy little noggins for fancy sensing and computing systems. Despite their small size, though, bees are able to perform precise flight maneuvers, and it's a good thing, too, since often their homes are on the other side of holes not much bigger than they are. Bees make this work through a sort of minimalist brute-force approach to the problem: They fly up to a small hole or gap, hover, wander back and forth a little bit to collect visual information about where the edges of the gap, and then steer themselves through. It's not fast, and it's not particularly elegant, but it's reliable and doesn't take much to execute.

Marketers have moved past merely producing effective creative messaging to striving to drive business growth. In the digital era, they're looking to data--and technologies such as machine learning--to predict and deliver on customers' needs.