An artificial intelligence system (AI) at the Massachusetts Institute of Technology has taken an IQ test designed for a young child. The results, written up by MIT Review, revealed that its IQ was equivalent to that of a four-year-old. Increasingly machines are getting better at specific tasks such as playing chess, recognising pictures and making complex commutations. But general intelligence is still proving elusive for most of them. The MIT machine - dubbed ConceptNet4 - was put through its paces by researchers from the University of Illinois, led by Stellan Ohlsson.

Beth Kutscher is based in Mountain View, Calif., and covers healthcare innovation and digital health. Before joining Modern Healthcare in 2012, she was a content editor and healthcare reporter for the New York-based Mergermarket Group. She previously was news and online editor for Pharmaceutical Executive and deputy news editor and healthcare reporter for PRWeek. She has a bachelor's degree in English from Cornell University.

I'm trying to get into neural networks. There have been a couple big breakthroughs in the field in recent years and suddenly my side project of messing around with programming languages seemed short sighted. It almost seems like we'll have real AI soon and I want to be working on that. While making my first couple steps into the field it's hard to keep that enthusiasm. A lot of the field is still kinda handwavy where when you want to find out why something is used the way it's used, the only answer you can get is "because it works like this and it doesn't work if we change it."

Does anyone know why I get this error when creating the ggplot for the train data set? Perhaps you want stat "count"?

Forget PC doldrums and waning smartphone demand. Google thinks computers will one day cease being physical devices. "Looking to the future, the next big step will be for the very concept of the'device' to fade away," Google chief executive officer Sundar Pichai wrote on Thursday in a letter to shareholders of parent Alphabet Inc. "Over time, the computer itself -- whatever its form factor -- will be an intelligent assistant helping you through your day." Instead of online information and activity happening mostly on the rectangular touch screens of smartphones, Pichai sees artificial intelligence (AI) powering increasingly formless computers. "We will move from mobile-first to an AI-first world," he said.

Data science is at the core of Amy Ingram, our AI personal assistant, and Data Scientists make up a big part of our team. To animate Amy (and her twin brother Andrew), we are teaching her to understand scheduling related emails. Teaching machines to parse natural language alone is a daunting challenge (and represents an entire field, Natural Language Processing or NLP). But that's not the end of it, because humans are not very precise communicators, even at our best. As a result, teaching Amy to successfully negotiate meeting times and locations for our beta customers has required collecting large amounts of data and applying some of the most advanced Machine Learning in the academy, stretching it beyond its usual boundaries.

Do they miss you when you're away on business? Can they put on a VR headset without their parents' help? That last one is pretty important. The year is zipping by, but before we launch full-force into next month, there's just about enough time for a quick roundup of the best updates and launches in April. It was recently revealed that Google was testing a new app for travelers, and now we have a better idea of what it might do.

With an ever-increasing volume of electronic data being collected by the healthcare system, researchers are exploring the use of machine learning--a subfield of artificial intelligence--to improve medical care and patient outcomes. An overview of machine learning and some of the ways it could contribute to advancements in plastic surgery are presented in a special topic article in the May issue of Plastic and Reconstructive Surgery, the official medical journal of the American Society of Plastic Surgeons (ASPS). "Machine learning has the potential to become a powerful tool in plastic surgery, allowing surgeons to harness complex clinical data to help guide key clinical decision-making," write Dr. Jonathan Kanevsky of McGill University, Montreal, and colleagues. They highlight some key areas in which machine learning and "Big Data" could contribute to progress in plastic and reconstructive surgery. Machine Learning Shows Promise in Plastic Surgery Research and Practice Machine learning analyzes historical data to develop algorithms capable of knowledge acquisition.

It is said of the ancient Chinese game go that the number of possible positions on its board exceeds the number of atoms in the known universe. This is old news, presumably, to masters of go and master mathematicians. To the rest of us it came as something of a shock when it became common knowledge in March, the occasion being the defeat -- shocking in itself -- of a world-ranking go master by a mere (so we would have said, once upon a time) computer. Or perhaps, giving it a positive spin, we should say "victory" instead of "defeat": a computer's victory over a mere human. What is the human brain to make of such facts?

When you think of artificial intelligence, the first image that likely comes to mind is one of sentient robots that walk, talk, and emote like humans. It's known as machine learning, and it revolves around enlisting computers in the task of sorting through the massive amounts of data that modern technology has allowed us to generate (a.k.a. One of the places machine learning is turning out to be the most beneficial is in the environmental sciences, which have generated huge amounts of information from monitoring Earth's various systems -- underground aquifers, the warming climate, or animal migration, for example. A slew of projects have been popping up in this relatively new field, called computational sustainability, that combine data gathered about the environment with a computer's ability to discover trends and make predictions about the future of our planet. This is useful to scientists and policy-makers because it can help them develop plans for how to live and survive in our changing world.