If you tell Siri to set an alarm for 5 am, she'll set an alarm for 5 am. But if you start asking her which prescription pain killer is least likely to upset your stomach, she's not really gonna know what to do--just because that's a pretty complicated sentence. Siri is a long way from what computer scientists call "natural language understanding." She can't truly understand the natural way we humans talk--despite the way Apple portrays her in all those TV ads. In fact, we shouldn't really be talking about her as a "her" at all.

A file photo dated 06 January 2004 shows Apple Computer's CEO Steve Jobs sitting in front of a project Apple Computer logo during his keynote speech at the MacWorld Expo in San Francisco, California, USA. Apple's (AAPL) epic fall on the markets took a symbolic turn Thursday after its market value again dropped below its top rival's. That makes it second fiddle behind Google parent Alphabet (GOOGL) at 497.8 billion. Shares of Apple have been in freefall this year, dropping more than 14%, amid the company's disappointing first-quarter results. It's the second time this year that Alphabet's market value has surpassed Apple's.

The "Hybrid Hydrostatic Transmission" system uses both fluid- and air-filled lines to control the movements of a telepresence robot. By combining the stiffness of fluid lines with the springiness and responsiveness of air-filled lines, the robot is able to move in a lifelike manner while providing constant, high-quality haptic feedback. "We have developed new rotary actuators using rolling-diaphragm cylinders which provide high torque density," the Disney Research team wrote, "and allow the creation of a new high-performance 10-DOF humanoid robot." While these new actuators are a bit bigger and heavier than conventional valve-based hydraulic systems, they do offer very low impedance. This means that the even bigger and heavier motor doesn't need to be mounted on the limb it's powering, which in turn reduces the amount of power needed to move it.

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.