Chinese ridesharing leader Didi Chuxing has opened a Silicon Valley research hub, where it will join the race with other tech companies for autonomous driving. The Didi Labs centre in Mountain View – which is also the home of Google – will focus on "intelligent driving technologies," according to a statement Wednesday. Building on rich data and fast-evolving AI (artificial intelligence) analytics, we will be working with cities and towns to build intelligent transportation ecosystems for the future," said Didi founder and chairman Cheng Wei. One of the engineers hired for the lab is Charlie Miller, who gained famed two years ago for hacking into a Jeep to show how automobiles can be taken over remotely. "My job is to make sure the assisted driving and autonomous systems developed and used by Didi are resistant to external attacks and threat," Miller, who has been working at Uber, said in a tweet.

Artificial Intelligence (AI) and machine learning will improve sales and marketing by enabling processes and communication without continuous direction. The addition of voice-first systems could eliminate much of the power of'push marketing'. Marketing and advertising have been around since the dawn of the Sumerian culture over 6,000 years ago. Marketing methods will be fundamentally altered with the rise of artificial intelligence, chatbots and the emergence of voice-first communication systems. Cloud computing provides an exponential increase in processing power, while advanced analytics has provided new ways to move from data to insight.

Plenty of animals communicate with one another, at least in a general way--wolves howl to each other, birds sing and dance to attract mates and big cats mark their territory with urine. But researchers at Tel Aviv University recently discovered that when at least one species communicates, it gets very specific. Egyptian fruit bats, it turns out, aren't just making high pitched squeals when they gather together in their roosts. According to Ramin Skibba at Nature, neuroecologist Yossi Yovel and his colleagues recorded a group of 22 Egyptian fruit bats, Rousettus aegyptiacus, for 75 days. Using a modified machine learning algorithm originally designed for recognizing human voices, they fed 15,000 calls into the software.

Perhaps in the future, artificial intelligence will intervene and write this article. Perhaps in the future, the editorial team will become redundant and ARN will embrace a form a robo-journalism. Perhaps in the future, it even won't matter, because the entire channel will also be unemployed. And what a different world it would be. For the rise of AI - as the world likes to categorise it - is storming along like a tech freight train, charging through barriers and racing towards a new world. Within this new world, will naturally be new ways to engage, conduct business and make money, creating opportunities and challenges for the channel in parallel.

If there's any doubt as to why "big data" has become as ubiquitous in business as pens, chairs and coffee mugs, look no further than the margins. Since becoming the buzzword of the decade, big data has given countless businesses huge competitive advantages by redefining the quality of the information at their fingertips and the speed at which they can react. So why have apparel brands lagged in doing the same? In many cases, identifying the "next big thing" -- what will sell, and the rate at which it will fly off the shelves -- is still steeped in guesswork and unsupported instinct. For brands, the use case is abundantly clear.

Too often, engineers are brainwashed into thinking they can create an impeccable artificial intelligence (AI) model -- a blank slate they release into the wild for independent learning. They think: "If I create flawless math on top of the right infrastructure, I'll have the perfect model." Train the algorithm, let it run free, and that's the end of the story, right? Just like human intelligence, artificial intelligence requires continuous learning to advance its expertise. Training a commercially applied AI is not a one-and-done exercise.

Machine learning is revolutionizing healthcare. Here are some highlights of interesting applications of how research in artificial intelligence is helping people. Habits are best changed in a group-support type setting. What these researchers accomplished was to create an AI based messaging platform that sends supportive messages to help people quit smoking. The way we move is a valuable insight to health and illness. People suffering from a stroke or parkinson for example have a certain pattern of moving.

How can people learn to work better with robots? First, have them watch robots on the silver screen. That's the finding of a recent study that had 56 undergraduate students rate their feelings toward humanlike service robots. Half of the group watched the science-fiction movie "Robot and Frank," which involved a robot, and the other half watched "Safety Not Guaranteed," a sci-fi romantic comedy that didn't involve robots, before they made their decision. The result: Those who viewed the movie with the robot were more likely to say that they would buy humanoid robots that assist the elderly.

In 2013, Alistair Shepherd asked everyone in a business-school pitch competition to complete a survey with questions inspired by online-dating sites. It asked things like "Do you like horror movies?" and "Do spelling mistakes annoy you?" Shepherd predicted how well the eight teams would collaborate internally and how they would ultimately fare. He ended up ranking all eight correctly. What made for a great team? Those in which people had the most tolerance for their teammates' perspectives--and those in which people had the greatest diversity in personalities. Mr. Shepherd's experiment represents an attempt to get beyond the usual approach to workplace chemistry.

The next assistant in many offices could be named Alexa or Cortana. In 2016, Silicon Valley obsessed over how text-based bots in apps like Slack could make employees more efficient, turning complicated tasks or forms into conversational texts. Now, following the success of Amazon Inc.'s Alexa and Alphabet Inc.'s Google Home, people in the technology industry are increasingly thinking about how such voice-activated devices can be made useful in the workplace. The workplace offers challenges that experts say intelligent assistants built for home use so far haven't effectively met, mostly in the area of voice recognition. Workers at Goodwinds Inc. in New York City, for example, have used an Amazon Echo attached to the office ceiling for such tasks as adding events to their calendars and setting reminders for meetings, says Vinay Patankar, chief executive of the workflow-management startup.