A natural language model developed in the Robotics and Artificial Intelligence Laboratory allows a user to speak a simple command, which the robot can translate into an action. If the robot is given a command to pick up a particular object, it can differentiate between other objects nearby, even if they are identical in appearance. Inside the University of Rochester's Robotics and Artificial Intelligence Laboratory, a robotic torso looms over a row of plastic gears and blocks, awaiting instructions. Next to him, Jacob Arkin '13, a doctoral candidate in electrical and computer engineering, gives the robot a command: "Pick up the middle gear in the row of five gears on the right," he says to the Baxter Research Robot. The robot, sporting a University of Rochester winter cap, pauses before turning, extending its right limb in the direction of the object.

Technically Incorrect offers a slightly twisted take on the tech that's taken over our lives. Perhaps you've been worried that someone will soon design a robot that can do your job. Yes, a robot that can play politics even better than you do. And, on a grander scale, what if a robot came along that could code even faster than Facebook's Mark Zuckerberg and be a slightly better speaker? Treasury Secretary Steve Mnuchin believes there's little reason to worry.

We've been losing the war on cybercrime for some time. Research firm Forrester reports over a billion accounts stolen in 2016 alone, and these data breaches are going up, not down. We are having to wade through more incident data, and people cannot keep up. Could machine learning help solve the problem? For years, researchers hoped that artificial intelligence would produce human-like machines.

A new global study finds several new categories of human jobs emerging, requiring skills and training that will take many companies by surprise. The threat that automation will eliminate a broad swath of jobs, across the world economy is now well established. As artificial intelligence (AI) systems become ever more sophisticated, another wave of job displacement will almost certainly occur. But here's what we've been overlooking: Many new jobs will also be created -- jobs that look nothing like those that exist today. In Accenture's global study of more than 1,000 large companies already using or testing AI and machine-learning systems, we identified the emergence of entire categories of new, uniquely human jobs.

AI is one the 2017's big buzzwords. The new technology is exciting and offers a plethora of possibilities that were once reserved solely for our wildest dreams and cinema screens. However, with the advancements in AI also comes fear. People are worried about how many jobs will be lost to artificial intelligence. PwC has released a new study centred on the future of the UK's economy.

Would your banking experience be more satisfying if you could gaze into the eyes of the bank's customer service chatbot and know it sees you frowning at your overdraft fees? Professor and entrepreneur Mark Sagar thinks so. Sagar won two Academy Awards for novel digital animation techniques for faces used on movies including Avatar and King Kong. He's now an associate professor at the University of Auckland, in New Zealand, and CEO of a startup called Soul Machines, which is developing expressive digital faces for customer service chatbots. He says that will make them more useful and powerful, in the same way that meeting someone in person allows for richer communication than chatting via text.

Businesses that put in the effort to create an artificially intelligent business may see amazing returns at first -- but there are good reasons to expect those to diminish. It would be very, very helpful to know what the future holds for artificial intelligence in business. Unfortunately, it is also very, very hard to predict. With this topic, our extrapolation heuristics may not work well. We tend to extrapolate linearly, expecting the pace of past progress to continue unchanged.

We explore the use of deep learning hierarchical models for problems in financial prediction and classification. Financial prediction problems – such as those presented in designing and pricing securities, constructing portfolios, and risk management – often involve large data sets with complex data interactions that currently are difficult or impossible to specify in a full economic model. Applying deep learning methods to these problems can produce more useful results than standard methods in finance. In particular, deep learning can detect and exploit interactions in the data that are, at least currently, invisible to any existing financial economic theory.

The world population is expected to reach 9.7 billion by 2050. China and India, the two largest countries in the world, have populations totalling around one billion. In four years, by 2022, India is predicted to have the largest population in the world, surpassing China. "My best employees are leaving," Daniel told me, "and I can't seem to figure out why." p Daniel (not his real name) was a VP human resource manager at a Fortune 500 company. I asked him whether he had collected any data that could provide him with insights into systematic patterns.

Today, in 2017, the president's top economic advisor said he had no worries about robots putting people out of work. "In terms of artificial intelligence taking over the jobs, I think we're so far away from that that it's not even on my radar screen," Treasury Secretary Steve Mnuchin told an audience in Washington. "I think it's 50 or 100 more years." President Trump can go back to horsing around on his big rig confident in the knowledge self-driving trucks won't replace millions of drivers in a few years. Artificial intelligence is not only coming for jobs, the jobs it's coming for are the precious few left over after old-school automation already came for so many others.