Peter Singer is a professor of bioethics at Princeton University and Laureate Professor at the University of Melbourne His books include Animal Liberation, The Life You Can Save, The Most Good You Can Do, and, most recently, Famine, Affluence and Morality. Last month, AlphaGo, a computer program specially designed to play the game Go, caused shock waves among aficionados when it defeated Lee Sedol, one of the world's top-ranked professional players, winning a five-game tournament by a score of 4-1. Why, you may ask, is that news? Twenty years have passed since the IBM computer Deep Blue defeated world chess champion Garry Kasparov and we all know computers have improved since then. But Deep Blue won through sheer computing power, using its ability to calculate the outcomes of more moves to a deeper level than even a world champion can.

Sure, robots and intelligent machines are likely to replace jobs in the not so distant future. The situation, though, isn't as dire as some would have you believe, according to Tom Davenport, co-author of Only Humans Need Apply: Winners and Losers in the Age of Smart Machines. The book is due out in May. Instead of stealing humans' jobs, artificial intelligent systems and robotics will help many people do their jobs better. "We have a new generation of technologies and we need to work with them if we're going to be productive and effective," Davenport said in an interview.

In the Army's Emergent Leader Immersive Training Environment, or ELITE, Soldiers hone their basic counseling skills through practice with virtual humans like virtual Staff Sergeant Jessica Chen. New research aims to get robots and humans to speak the same language to improve communication in fast-moving and unpredictable situations. Scientists from the U.S. Army Research Laboratory and the University of Southern California Institute for Creative Technologies are exploring the potential of developing a flexible multimodal human-robot dialogue that includes natural language, along with text, images and video processing. "Research and technology are essential for providing the best capabilities to our Warfighters," said Dr. Laurel Allender, director of the U.S. Army Research Laboratory Human Research and Engineering Directorate. "This is especially so for the immersive and live-training environments we are developing to achieve squad overmatch and to optimize Soldier performance, both mentally and physically."

One week ago, I asked Facebook's Messenger to send me the weather forecast every morning. It has yet to do so. Messenger is supposed to deliver me the weather through a free service called Poncho, one of the first "chat bots" to live inside Facebook's messaging app behemoth. Instead of checking the weather through an app like Dark Sky or even Poncho's own iPhone app, Poncho's playful Messenger bot is designed to chat with me about the weather like a human being. Poncho's bot has not only failed to send me the weather like I asked, but its bot has so far proven to be the most complicated method of getting the weather imaginable.

Research funded by the National Science Foundation may have found an ingenious solution to poaching: applying game theory and computer science to real-life situations. One of the biggest factors in why there are so many endangered animals today is poaching – a centuries-old problem. The dwindling tiger population is one of the most glaring examples of this. Whether for sport, medicine, pelts or other body parts, poaching remains a huge threat to wildlife. Patrols have long been the most direct form of human intervention in wildlife protection.

Computer chip giant Nvidia has developed a "miracle" chip that is expected to significantly accelerate breakthroughs in artificial intelligence research. Nvidia's Tesla P100 chip crams in 15 billion transistors within its 610-square-millimeter frame, around three-times more than most processors or graphics chips on the market. According to the company's CEO, this makes the Tesla P100 the largest computer chip ever made. "Three years ago, we dedicated ourselves on the single greatest endeavour in the history of our company," Jen-Hsun Huang, CEO of Nvidia, said at the GPU Technology Conference earlier this month. "We decided to be all in on AI. For the first time, we would design [a chip] that is dedicated to this field of work. Dedicated to accelerating AI; dedicated to accelerating deep learning. "I think we are going to realize looking back that one of the biggest things that ever happened is AI." The Tesla P100 is the product of around 2.5 billion worth of research and development at the hands of thousands of computer engineers. The Tesla P100 chip contains more than 15 billion transistors and is described by Nvidia's CEO as "a beast of a machine." "The odds of this working at all is approximately zero," said Huang. "We are changing so many things in one project.

See Sea Hunter hunt submarines. Was it really only December that DARPA told us it was building a submarine-hunting drone-ship for the Navy? Well, get ready to be surprised. Just four months after we learned of the existence of the Anti-Submarine Warfare Continuous Trail Unmanned Vessel program, or ACTUV, it's already complete -- and afloat. Last week, the Pentagon's mad scientists at the Defense Advanced Research Projects Agency unveiled the ACTUV prototype in Portland, Ore., christening the vessel Sea Hunter.

The world's biggest technology companies are handing over the keys to their success, making their artificial intelligence systems open-source. Traditionally, computer users could see the end product of what a piece of software did by, for instance, writing a document in Microsoft Word or playing a video game. But the underlying programming -- the source code -- was proprietary, kept from public view. Opening source material in computer science is a big deal because the more people that look at code, the more likely it is that bugs and long-term opportunities and risks can be worked out. Openness is increasingly a big deal in science as well, for similar reasons.

In the race to develop self-driving cars, the United States and Europe lead in technology, but China is coming up fast in the outside lane with a regulatory structure that could put it ahead in the popular adoption of autonomous cars on its highways and city streets.

Over the last several decades, the digital revolution has changed nearly every aspect of our lives. The pace of progress in computers has been accelerating, and today, computers and networks are in nearly every industry and home across the world. Many observers first noticed this acceleration with the advent of modern microchips, but as Ray Kurzweil wrote in his book The Singularity Is Near, we can find a number of eerily similar trends in other areas too. According to Kurzweil's law of accelerating returns, technological progress is moving ahead at an exponential rate, especially in information technologies. This means today's best tools will help us build even better tools tomorrow, fueling this acceleration.