But by a fortuitous coincidence, a related type of computer chip, called a graphic processing unit, or GPU, turns out to be very effective when applied to the types of calculations needed for neural nets. In fact, speedups of 10X are not uncommon when neural nets are moved from traditional central processing units to GPUs. GPUs were initially developed to rapidly display graphics for applications such as computer gaming, which provided scale economies and drove down unit costs, but an increasing number of them are now used for neural nets. As neural net applications become even more common, several companies have developed specialized chips optimized for this application, including Google's tensor processing unit, or TPU.
In this guest post, Jacqueline M. Kory Westlund, a researcher in the Personal Robots Group at the MIT Media Lab describes her projects and explorations to understand children's relationships with social robots. What design features of the robots affect children's learning--like the expressivity of the robot's voice, the robot's social contingency, or whether it provides personalized feedback? When I tell people about the Media Lab's work with robots for children's education, a common question is: "Are you trying to replace teachers?" Despite all the research that seems to point to the conclusion "robots can be like people," there are also studies showing that children learn more from human tutors than from robot tutors.
Natural Language Processing (NLP) of texts has been applied with different degrees of success. Thus, new NLP interesting applications appear such as sentiment analysis (extracting opinions in a user opinion about a product), user wants and needs detection or user profiling. High-level abstraction of texts: Deep Learning technologies wisely combine the aforementioned word representations to obtain a semantic view of more complex texts such as sentences and documents. With this information, computers can take a grasp of the real meaning of texts obtaining better results in comparison with traditional approaches when complex analysis are involved (sentiment analysis, automatic translation, detection of entities in texts, question-answering system, etc).
David Levy is an International Chess Master and a prolific chess writer. He became famous in the computer world as a result of a bet, started in 1968, that he would not lose a chess match against a computer program within 10 years - in 1978 he won the bet which then stood at £1,250. His computing career began at Glasgow University, where he taught Algol programming and Artificial Intelligence during the early 1970s. He is widely regarded as one of the world's leading authorities on computer chess, and is Chairman of a London-based software house which specializes in programming intelligent games.
Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) believe that analyzing photos like these could help us learn recipes and better understand people's eating habits. In a new paper with the Qatar Computing Research Institute (QCRI), the team trained an artificial intelligence system called Pic2Recipe to look at a photo of food and be able to predict the ingredients and suggest similar recipes. "In computer vision, food is mostly neglected because we don't have the large-scale datasets needed to make predictions," says Yusuf Aytar, an MIT postdoc who co-wrote a paper about the system with MIT Professor Antonio Torralba. The CSAIL team's project aims to build off of this work but dramatically expand in scope.
This conversation occurred between two AI agents developed inside Facebook. As these two agents competed to get the best deal–a very effective bit of AI vs. AI dogfighting researchers have dubbed a "generative adversarial network"–neither was offered any sort of incentive for speaking as a normal person would. As Dauphin points out, machines might not think as you or I do, but tokens allow them to exchange incredibly complex thoughts through the simplest of symbols. In other words, machines allowed to speak and generate machine languages could somewhat ironically allow us to communicate with (and even control) machines better, simply because they'd be predisposed to have a better understanding of the words we speak.
Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) believe that analyzing photos like these could help us learn recipes and better understand people's eating habits. In a new paper with the Qatar Computing Research Institute (QCRI), the team trained an artificial intelligence system called Pic2Recipe to look at a photo of food and be able to predict the ingredients and suggest similar recipes. "In computer vision, food is mostly neglected because we don't have the large-scale datasets needed to make predictions," says Yusuf Aytar, an MIT postdoc who co-wrote a paper about the system with MIT Professor Antonio Torralba. They then used that data to train a neural network to find patterns and make connections between the food images and the corresponding ingredients and recipes.
Former world chess champion Garry Kasparov is long overdue for telling his side of the story regarding his famous match with the IBM computer Deep Blue in May 1997. In the new book Deep Thinking, Kasparov and longtime writing partner Mig Greengard intertwine his experiences--before, during, and after the match--with a historical overview of chess-playing AI to produce a well-written, accessible book that provides food for thought about our future alongside increasingly intelligent machines. Many in the chess community, who may buy the book for insight into the match's outcome, will be surprised to see a side of Kasparov that the general public has not seen before--a man who has mellowed over time. Those in the artificial-intelligence and technology communities may buy this book because of the intriguing tag line "Where machine intelligence ends and human creativity begins."
Right now, Aira's customers share their video streams with people--Aira calls them "agents"--who work on a model like Uber, with the ability to log on, pick up a user's call, and get paid for the hours they work. The same technology that powers computer vision projects at Google and Facebook and Pinterest could one day tell Hingson where he left his house keys, or read the street signs at an intersection, or recognize which of his friends are in the room. The system translates visual information from a small camera mounted on sunglasses onto a surgically implanted retinal device, which creates electrical pulses inside the eye. The device, called BrainPort, picks up light signals from the camera mounted on a set of sunglasses and translates it into electrical pulses on a tiny electric "lollipop."
Japan's On-Art Corp's CEO Kazuya Kanemaru poses with his company's eight metre tall dinosaur-shaped mechanical suit robot'TRX03' and other robots during a demonstration in Tokyo, Japan Japan's On-Art Corp's eight metre tall dinosaur-shaped mechanical suit robot'TRX03' performs during its unveiling in Tokyo, Japan Singulato Motors co-founder and CEO Shen Haiyin poses in his company's concept car Tigercar P0 at a workshop in Beijing, China A picture shows Singulato Motors' concept car Tigercar P0 at a workshop in Beijing, China Connected company president Shigeki Tomoyama addresses a press briefing as he elaborates on Toyota's "connected strategy" in Tokyo. A Toyota Motors employee demonstrates a smartphone app with the company's pocket plug-in hybrid (PHV) service on the cockpit of the latest Prius hybrid vehicle during Toyota's "connected strategy" press briefing in Tokyo An employee shows a Samsung Electronics' Gear S3 Classic during Korea Electronics Show 2016 in Seoul, South Korea Visitors experience Samsung Electronics' Gear VR during the Korea Electronics Grand Fair at an exhibition hall in Seoul, South Korea Amy Rimmer, Research Engineer at Jaguar Land Rover, demonstrates the car manufacturer's Advanced Highway Assist in a Range Rover, which drives the vehicle, overtakes and can detect vehicles in the blind spot, during the first demonstrations of the UK Autodrive Project at HORIBA MIRA Proving Ground in Nuneaton, Warwickshire Chris Burbridge, Autonomous Driving Software Engineer for Tata Motors European Technical Centre, demonstrates the car manufacturer's GLOSA V2X functionality, which is connected to the traffic lights and shares information with the driver, during the first demonstrations of the UK Autodrive Project at HORIBA MIRA Proving Ground in Nuneaton, Warwickshire In its facilities, JAXA develop satellites and analyse their observation data, train astronauts for utilization in the Japanese Experiment Module'Kibo' of the International Space Station (ISS) and develop launch vehicles The robot developed by Seed Solutions sings and dances to the music during the Japan Robot Week 2016 at Tokyo Big Sight. PCs featuring the Atom Z2760, Atom Z2520, Atom Z2560 and Atom Z2580 processors have been found to be incompatible with the Windows 10 Creators Update, and Microsoft has now revealed that they will not be able to install any other Windows 10 updates. "This is the case with devices utilizing Intel Clover Trail Atom Processors today: they require additional hardware support to provide the best possible experience when updating to the latest Windows 10 feature update, the Windows 10 Creators Update.