Amazon is eager to get more bright minds working on voice technology, so it's expanding the Alexa Fellowship program to 14 more universities, including Massachusetts Institute of Technology, Texas A&M and Cambridge. The fellowships are financed through Amazon's $200 million Alexa Fund. Other schools joining the roster include University of Texas at Austin, Dartmouth, Arizona State and the International Institute of Information Technology in Hyderabad, India. The latest additions take the number of schools in the program to 18, joining the previous quartet of Carnegie Mellon, University of Southern California, Johns Hopkins and Waterloo. The program comprises two different fellowships: Alexa Graduate Fellowship and Alexa Innovation Fellowship.

English-speaking artificial intelligence (AI) robots will be helping out in some 500 Japanese classrooms from next year as the country seeks to improve its English skills, particularly among children and teachers. The education ministry is planning a pilot project costing around 250 million yen (US$227,000) to improve Japanese students' notoriously weak oral and written English, an official said. "AI robots already on the market have various functions. For example, they can check the pronunciation of each student's English, which is difficult for teachers to do," said the official in charge of international education, who asked not to be named. AI robots "are just one example of the trial and we are planning other measures" such as using tablet apps and having online lessons with native speakers, he said.

Researchers at the University of Wisconsin-Madison have built a robot, named Minnie, to serve as a reading buddy to middle school kids, and Minnie's new friends grew more excited about books and more attached to the robot over two weeks of reading together. "After one interaction, the kids were generally telling us that, sure, it was nice to have someone to read with," says Joseph Michaelis, a UW-Madison graduate student studying educational psychology. "But by the end of two weeks, they're talking about how the robot was funny and silly and afraid, and how they'd come home looking forward to seeing it again." Michaelis and computer sciences professor Bilge Mutlu published their work with Minnie on Wednesday (Aug. Research shows that social learning -- pairing up with a peer to complete math problems or read a chapter in a textbook -- is a powerful way to help students develop skills and interests, according to Michaelis.

One of the questions I get asked most frequently is how I so quickly changed from a "plain old software engineer" to "certified Data Scientist" as quickly as I did. While I do plan to write a book/shoot a video on the topic. In the meantime, enjoy this video from Siraj Raval where he shows the techniques he uses to study machine learning. That includes living a healthy lifestyles, optimizing your learning environment, creating a personalized learning path, prioritizing effectively, and being an active learner. He demos the FAST technique, which you can use to help learn faster and more efficiently.

Earlier this year, I witnessed a scene out of science fiction, had it not been reality. A video shown at the NewSchools Venture Fund annual conference showed a young African-American girl answering a teacher's questions with confidence, enthusiastic to get them right. The girl was real, but the teacher was not. She was a virtual instructor named "ALEX," powered by Artificial Intelligence (AI). The virtual being was programmed to use an African-American dialect.

The University of Hong Kong (HKU) announced that it had signed a memorandum of understanding (MoU) with Microsoft Hong Kong in May 2018 to form an Artificial Intelligence (AI) research partnership to incubate talent and encourage breakthroughs in various sectors by accelerating scientific progress and enabling data-driven research. Commenting on the memorandum, Professor Andy Hor, Vice-President, and Pro-Vice-Chancellor (Research), University of Hong Kong stated HKU was glad to join hands with Microsoft in this AI partnership to enable the professionals and researchers at HKU to apply AI in research projects. Prof Andy noted that Healthcare and Fintech are the key industries in Hong Kong and that through this collaboration with the company, HKU students have the chance to equip themselves with knowledge of Data Science and AI. This will enable researchers to accelerate their professional development, she added. Cally Chan, General Manager of Microsoft Hong Kong said that the company's mission is to empower their partners in different industries to take a significant leap forward in accelerating digital transformation and achieve more.

It's hard to make a case for the "sudden" development of something that has been a formal topic of research for more than 60 years. Attending presentations on Artificial Intelligence (AI) at three recent conferences and following that up with extensive reading does, however, suggest that all of us engaged in teaching-training-learning need to be familiar with recent AI developments and projects that are rapidly changing our world. The April 2018 Unconference for Dreamers, Doers, and Drivers Shaping the Future of Learning, held on an Arizona State University campus and previously discussed here on the Top of Mind blog by The Tambellini Group Senior Analyst Alex Freeman, paid ample attention to AI. Developments in all three areas are continuing to open doors to potential collaborations between learning facilitators, learners, and machines in ways that may foster more dynamic, engaging, and results-oriented learning experiences for those we serve in our lifelong-learning environments. Examples cited by Keller include customizable learning experiences, student-persistence prediction, unbiased grading systems, more sophisticated and useful teacher-student performance analytics, suggested learning paths, better ways of matching students and teachers in learners' moments of need, and detecting fraudulent activity in the learning process. Unconference participants walked away from Keller's presentation and their subsequent explorations of the topic with a commitment to "design blueprints for an AI-enabled virtual assistant for teaching, learning and advising, factoring in expanded functionalities over the next 5, 10, and 20 years," the ShapingEDU "10 Actions to Shape the Future of Education" communique confirms.

The UK has a genuine opportunity to take a lead on the ethics of artificial intelligence, says Nigel Shadbolt, principal of Jesus College, Oxford and co-founder of the Open Data Institute (ODI). You forgot to provide an Email Address. This email address doesn't appear to be valid. This email address is already registered. You have exceeded the maximum character limit.

Curtin University, in Western Australia, will be working with Optus Business as they form a research group that will focus on the impact of artificial intelligence (AI) on regional telecommunications, higher education and the urban environment. According to the report made by the University, an artificial intelligence research group will be formed from the five-year alliance. The group will be embedded in the School of Electrical Engineering, Computing and Mathematical Sciences at the University, having strong links to the Curtin Institute for Computation. The excellent research, teaching and learning capabilities of the University will be synergised with the market-leading technology and infrastructure capabilities of the telco company and will be fully leveraged by the alliance of both. The research group will involve the appointment of an Optus Chair in Artificial Intelligence and three Optus Research Fellows focusing on applying artificial intelligence technologies in areas such as regional telecommunications, improving higher education student outcomes and the urban environment.

In treatment allocation problems the individuals to be treated often arrive sequentially. We study a problem in which the policy maker is not only interested in the expected cumulative welfare but is also concerned about the uncertainty/risk of the treatment outcomes. At the outset, the total number of treatment assignments to be made may even be unknown. A sequential treatment policy which attains the minimax optimal regret is proposed. We also demonstrate that the expected number of suboptimal treatments only grows slowly in the number of treatments. Finally, we study a setting where outcomes are only observed with delay.