Artificial intelligence is an evolving field that requires broad training, so courses typically involve principles of computer science, cognitive psychology and engineering. These are the best artificial intelligence programs. Sign up for Grad Compass to get complete access to U.S. News rankings and school data.

For three decades, Mr. Phillips had focused on writing software to allow computers to understand human speech. In 2006, he had co-founded a voice recognition company, and eventually executives at Apple, Google and elsewhere proposed partnerships. Mr. Phillips's technology was even integrated into Siri itself before the digital assistant was absorbed into the iPhone. But in 2008, Mr. Phillips's company, Vlingo, had been contacted by a much larger voice recognition firm called Nuance. "I have patents that can prevent you from practicing in this market," Nuance's chief executive, Paul Ricci, told Mr. Phillips, according to executives involved in that conversation. Mr. Ricci issued an ultimatum: Mr. Phillips could sell his firm to Mr. Ricci or be sued for patent infringements. When Mr. Phillips refused to sell, Mr. Ricci's company filed the first of six lawsuits. Soon after, Apple and Google stopped returning phone calls. The company behind Siri switched its partnership from Mr. Phillips to Mr. Ricci's firm. And the millions of dollars Mr. Phillips had set aside for research and development were redirected to lawyers and court fees. When the first lawsuit went to trial last year, Mr. Phillips won.

Last August, Sebastian Thrun, the brains behind Google's self-driving cars and one of the world's top AI experts, offered an online version of Stanford's Introduction to Artificial Intelligence course to absolutely anyone who wanted to take it, for free. It turned out to be just a little bit popular (over 150,000 students enrolled), and now Thrun is offering a new, totally free, seven-week online course called Programming a Robotic Car. Can I really learn how to build a self-driving car in 7 weeks? In seven weeks, you will learn the basics of all the primary systems involved in programming a robotic car. Mad props to Professor Thrun for staying focused on the camera and barely glancing once at where the car was taking him.

The Computer Vision and Robotics Research (CVRR) Laboratory at the University of California, San Diego offers an unique and stimulating environment to graduate students, faculty members, and visiting scholars/collaborators to pursue a wide spectrum of research studies in the Sensor-Based Intelligent Systems area. The major thrust of our research is on developing a clear understanding of the computational and engineering related issues underlying the perception, planning, and control mechanisms for completely autonomous or semi-autonomous operation of integrated systems. The core group of researchers in the laboratory includes over a dozen graduate students, four research faculty members, and three adjunct faculty members. The academic program of the laboratory is primarily associated with the Electrical and Computer Engineering Department. Ties with Mechanical Engineering, Computer Science, Cognitive Science, Bioengineering, Structural Engineering, Scripps Institution of Oceanography, San Diego Supercomputing Center, and Salk Institute (Neuroscience) exists for interdisciplinary projects.

We describe a variety of projects developed as part of a course in Artificial Intelligence at the University of Minnesota. The projects cover navigation of small mobile robots and learning to accomplish simple tasks, and require a variety of approaches from neural networks to genetic programming to reactive behaviors. The projects have all been implemented on real robots. We discuss how the combination of robotics with Artificial Intelligence adds value to the learning of AI concepts and how the fun of building and programming a robot is a highly motivating force for the learning process. 1 Introduction The major goal of this paper is to describe examples of integration of real robotics projects in a course in Artificial Intelligence. The examples presented here are some of the class projects done by students taking a course in Artificial Intelligence at the University of Minnesota.

Eleven teams, including universities, defense contractors and small companies, are competing in the British Ministry of Defense's Grand Challenge with autonomous information-gathering vehicles that include flying saucers, a mini tank, several mini-helicopters and darts, among other machines. The winner of the competition, which launched Friday, will get a trophy and a potential contract with the Ministry of Defense. The multi-day challenge, the British response to the U.S. DARPA Grand Challenge, is taking place in a facsimile of a deserted German village built during the Cold War. The village serves as a training center for British troops, The Guardian reported. During the competition, the robots have to identify threats such as potential snipers and enemy vehicles and other threats, with minimal human guidance.

Summary: In which we attempt to answer the question, how does someone in school or recently out enter the exciting world of data science. There is no question that comes up more frequently than'how do I become a data scientist'. I've actually written several articles on this topic (and will reference them liberally in this post) but they lacked the global perspective that potential new entrants to data science want. I'm going to try to resolve here. I thought about changing the title to "Doing Data Science" instead of becoming a Data Scientist to focus on the activity and not just the job title.

This week's top Machine Learning stories, with a special focus on how deep learning is changing the world! Machine Learning is one of the most exciting fields in the world. Every week we discover something new, something amazing, something revolutionary. It's incredible, but it can also be overwhelming. That's why we created This Week in Machine Learning!

The child of a refugee from Vietnam is striving to realize her dream of building a Japanese language school in the Southeast Asian country. "My dream is to do something that would serve as a bridge between Japan and Vietnam," said Doan Thy Trang, 27. To achieve that goal, she founded a consulting firm in Akashi, a city in Hyogo Prefecture facing the Seto Inland Sea, in January 2015. Trang explained that many business trainees from Vietnam she meets through her work have little difficulty communicating with Japanese in daily conversations but struggle with technical terms. "Vietnamese need a school that teaches them Japanese language used in workplaces," she said.

This week we are celebrating Computer Science Education Week around the globe. In this "age of acceleration," in which advances in technology and the globalization of business are transforming entire industries and society itself, it's more critical than ever for everyone to be digitally literate, especially our kids. This is particularly true for women and girls who, while representing roughly 50 percent of the world's population, account for less than 20 percent of computer science graduates in 34 OECD countries, according to this report. This has far-reaching societal and economic consequences. One issue sometimes cited for the dearth of women in computing fields is the lack of professional role models who could inspire girls to pursue their STEM dreams. We've attempted to counteract this by asking 17 women within Microsoft's global research organization their views on what's likely to occur in their fields in 2017.