Vikash Kumar and University of Washington colleagues have developed a simulation model that allows robotic hands to learn from their own experiences, while performing dexterous manipulation. Human direction is not required. A recent study incorporated the model while a robotic hand attempted several tasks, including rotating an elongated object. With each try, the hand became better able to spin the tube. Machine learning algorithms helped it model the basic physics involved, and plan the actions it should take to best complete the task.

But such is not the case in the domain of cybersecurity. Although security solutions based on unsupervised machine learning do exist, relying entirely on artificial intelligence to spot cyberattacks isn't totally practical because such systems yield a large number of false positives. You eventually need the help of human experts to find evidence of security breaches and make critical decisions. This means cybersecurity professionals get to keep their jobs--at least for the time being. But that's not necessarily a good thing, especially since analyst-based security solutions are fraught with problems, too, and can't keep up with the huge volume of data that needs to be analyzed at every moment, eventually leading to high rates of undetected attacks and delayed responses.

Facebook says chatbots will change the way businesses communicate with their customers, but will businesses want to put their user communications in the hands of artificial intelligence? "They're a powerful tool but they're also a big risk," said Brian Blau, an analyst with Gartner. "A.I. can be a very powerful technology. Businesses are going to have to understand how to harness that power. There are reasons to be worried about it. Because we're giving chatbots the power to act on our behalf, they're taking on greater importance."

Artificial Intelligence (AI) "voices" listen, react and integrate with consumer devices. How can brands tap into this, and how can it benefit consumers? The absence of screens and the presence of a new voice is the reality of AI in the home. The Amazon Echo (fondly known as Alexa) listens and reacts to whomever is talking to it. Alexa will let you know how much food is in your fridge, check your work calendar, and answer almost any question.

One day in January, Eric Wilson dashed off a message to the teaching assistants for an online course at the Georgia Institute of Technology. "I really feel like I missed the mark in giving the correct amount of feedback," he wrote, pleading to revise an assignment. Thirteen minutes later, the TA responded. "Unfortunately, there is not a way to edit submitted feedback," wrote Jill Watson, one of nine assistants for the 300-plus students. Last week, Mr. Wilson found out he had been seeking guidance from a computer.

Nvidia researchers have created a convolutional neural network which has learned the rules of the road by observing video from cars operated by human drivers. The achievement demonstrates one reason there's so much excitement about artificial intelligence in the tech industry at the moment: When AI systems can learn, they require less programming. Danny Shapiro, Nvidia's senior director of automotive, said in a blog post that the company wanted to create a robust system for driving on public roads without the need to write code to handle every specific condition a driver might encounter, a requirement he considers impractical. Nvidia's nine-month-old project, dubbed DAVE2, represents an effort to expand on DARPA Autonomous Vehicle (DAVE) research, which aimed to create a system that could navigate public roads. DAVE ran from September 2003 through June 2004.

Join us live with Marcus Lemonis at Thought Leaders Arizona on May 24. We've all heard it by now: Data scientists have the century's sexiest job and they're here to save your business with their big data expertise. Everyone wants to hire one. But what are the chances you'll stumble across an actual data scientist unicorn who just happens to be a perfect fit for your business? The thing about data science is that it draws from dozens of fields, including machine learning, data mining, analytics and artificial intelligence.

Wi-Fi has moved from a nascent technology to one that is widely accepted and become so commonplace that we wonder how we ever functioned without it. It started from autonomous access points and was followed up by controller-based architecture (with a centralized controller and thin access points). And, as we learned from the challenges in deploying Wi-Fi and the ability of the environment to impact user experience, companies have constantly tried to innovate. Some focused on building dynamic channel or power planning, some built controller-less networks, and others tried to make it work in single channel. Of course, the discussion around the evolution of Wi-Fi architectures is not complete without talking about the adaptive beamforming antenna technologies.

This week we take a look at some recent developments in the realms of personalized shopping and artificial intelligence (AI) in ecommerce. Retailers, digital marketplaces, social networks and department stores are all trying to figure out the best way to deliver personalized, data-driven customer experience. Many companies see artificial intelligence as the answer to improve the shopping interface and user experience, while other marketers turn to personalized targeting methods and omni-channel strategies. In exploring these technological advances, it must be understood that not all innovations are profitable. These ideas have promises and risks, and their efficacy will ultimately be tested and decided by the customer. Last week, eBay acquired Expertmaker, a Swedish company that focused on artificial intelligence, machine learning and big data analytics.

In its quest to maintain a United States military advantage, the Pentagon is aggressively turning to Silicon Valley's hottest technology -- artificial intelligence. On Wednesday, Secretary of Defense Ashton B. Carter made his fourth trip to the tech industry's heartland since being named to his post last year. Before that, it had been 20 years since a defense secretary had visited the area, he noted in a speech at a Defense Department research facility near Google's headquarters. The Pentagon's intense interest in A.I. -- and by connection the Silicon Valley companies specializing in that technology -- has grown out of the "Third Offset" strategy articulated by Mr. Carter last fall. Concerned about the re-emergence of China and Russia as military competitors, he stated that computer-based, high-tech weapons would give the American military an edge in the future.