On a summer day four years ago, a Stanford University computer-science professor named Andrew Ng held an unusual air show on a field near the campus. His fleet of small helicopter drones flew under computer control, piloted by artificial-intelligence software that could teach itself to fly after watching a human operator. By the end of the day, the copters were hot-dogging--flipping, rolling, even hovering upside down. It was a milestone for the field of "machine learning," the same area of artificial intelligence that lets Amazon recommend books based on a shopper's previous habits and helps Google tailor search results to a user's behavior. Mr. Ng and his team of graduate students showed that artificial-intelligence software could control one of the hardest-to-maneuver vehicles and keep it stable while flying at 45 miles an hour.

The scientist behind Google Glass wearable technology has criticised the use of restrictive and "fear-based" testing regimes in education, describing a lack of innovation in the system as a crisis. Sebastian Thrun, who led the Google research lab responsible for self-driving cars and Google Glass, made the comments ahead of a meeting with education minister Michael Gove. Thrun, who is one of the world's most influential computer scientists, is exploring online collaborative education – known as Moocs, which stands for "massively open online courses". He has developed a project called Udacity, which is working with two colleges and workplace learning schemes. "The education system is based on a framework from the 17th and 18th century that says we should play for the first five years of life, then learn, then work, then rest and then die. I believe we should be able to do all those things all the time," said Thrun.

Soon they will be sophisticated enough to fill certain faculty roles at traditional universities. But to make this revolution work for students, academic leaders at those traditional institutions will need to broker a peace between artificially intelligent teaching programs and their human counterparts, according to a new report written by the former presidents of two prominent traditional universities on behalf of the nonprofit Ithaka S R. Online education has enabled many colleges to transition into the prevailing modern medium while adding new sources of revenue in times of scarcity, according to the Ithaka report. However, these innovative colleges have shown less interest in using the novel medium to curb tuition charges and measure learning outcomes. The report, called "Barriers to Adoption of Online Learning Systems in U.S. Higher Education," was co-written by Lawrence S. Bacow and William G. Bowen, the former presidents of Tufts and Princeton Universities, respectively, along with several Ithaka analysts. It was bankrolled by the Bill & Melinda Gates Foundation.

In his 10-week course Ng takes a an engineering-oriented approach to Machine Learning that concentrates on statistical models. If you are looking for an alternative Coursera also has Neural Networks for Machine Learning, a class taught by University of Toronto professor, Geoffry Hinton who is a leading proponent in the field from a cognitive science perspective. His eight-week course sets out to teach students artificial neural networks and how they're being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion. Its prerequisites are programming proficiency in Matlab, Octave or Python, plus knowledge of calculus, linear algebra and probability theory.

Anant Agarwal is a professor of electrical engineering and computer science at the Massachusetts Institute of Technology and president of edX, a leading provider of massive open online courses, known as Moocs. Created by the Massachusetts Institute of Technology and Harvard, edX is a non-profit, "open-source" organisation. Everybody should have access to a high-quality education. At edX we are applying technology to improve education in quality, scale and accessibility. We have about 1m people enrolled in edX.

In recent years, there's been no shortage of criticism that employers aren't providing enough of the training their workforces need to compete in the information economy. So here's some more fuel for this particular fire: executives report they'll probably need to "train" machines as much as they need to train people. A new survey of 2,000 business and IT executives from Accenture finds that more than three-fourths, 77 percent, believe that within three years, they will need to focus on training their machines as much as they do on training their employees. This kind of "training" involves the use of intelligent software, algorithms and machine learning. The same number of executives say they expect employees and intelligent machines to increasingly work side by side, in a collaborative way.

Virtual learning programs could soon mark the end of test-taking. Researchers from Stanford University and Google in California have developed a new algorithm that aims to understand students' individual learning abilities. The system can even predict whether the students will get questions right or wrong in a given exercise, and as development progresses, it may be also able to identify why they've chosen that way. Virtual learning programs could soon mark the end of test-taking. Researchers from Stanford University and Google in California have developed a new algorithm that can understand students' individual learning abilities.

To some degree, that's inevitable: Many people who enroll in MOOCs may have no interest in doing homework, but simply plan to listen to video lectures in their spare time. Others, however, may begin courses with the firm intention of completing them but get derailed by life's other demands. Identifying those people before they drop out and providing them with extra help could make their MOOC participation much more productive. The problem is that you don't know who's actually dropped out -- or, in MOOC parlance, "stopped out" -- until the MOOC has been completed. One missed deadline does not a stopout make; but after the second or third missed deadline, it may be too late for an intervention to do any good.

MIT President L. Rafael Reif announced today a significant expansion of the Institute's programs in learning research and online and digital education -- from pre-kindergarten through residential higher education and lifelong learning -- that fulfills a number of recommendations made in 2014 by the Institute-Wide Task Force on the Future of MIT Education. Most notably, Reif announced the creation of the MIT Integrated Learning Initiative (MITili), to be led by Professor John Gabrieli, and a new effort to increase MIT's ability to improve science, technology, engineering, and mathematics (STEM) learning by students from pre-kindergarten through high school (pK-12), to be led by Professor Angela Belcher. The announcement also included a program to support faculty innovations in MIT residential education and new work to enhance MIT's continuing education programs. In keeping with the high priority of these new efforts and of the entire field of digital learning, Professor Sanjay Sarma, now dean of digital learning, will oversee them in the newly created position of vice president for open learning, reporting directly to Reif. Chancellor Cynthia Barnhart, who will share responsibility with Sarma for several aspects of this work, predicts that the programs announced today will have "far-reaching and tremendous implications for education -- for MIT students as well as for students not at MIT."

Greater compute power and power efficiency has made deep learning algorithms ubiquitous in our world. Deep learning has found its way into self driving cars, convenience stores and hospitals. Yet the fight for top talent in the space remains fierce and is a bottleneck for reaching new industries and solving tough challenges. To complement Udacity's previous AI courses, the online education startup is partnering with YouTube star Siraj Raval for a new deep learning nanodegree foundation program that will be co-taught with Udacity's Mat Leonard. Foundation Programs are going to be a major focus for Udacity in the coming year.