Course Description Caffe is a deep learning framework made with expression, speed, and modularity in mind. Audience This course is suitable for Deep Learning researchers and engineers interested in utilizing Caffe as a framework. After completing this course, delegates will be able to: understand Caffe's structure and deployment mechanisms carry out installation / production environment / architecture tasks and configuration assess code quality, perform debugging, monitoring implement advanced production like training models, implementing layers and logging

This piece is the first in a series, called "Machine Learning Is Not Magic," covering how to get started in machine learning, using familiar tools such as Excel, Python, Jupyter Notebooks and machine learning cloud services from Azure and Amazon Web Services. Check back here each Friday for future installments. Back in 2010, when I first encountered the concept of Machine Learning (ML), I told myself that it is only for PhDs in Computer Science, which meant that I might never get a chance to work on it. As an ex-Microsoftie and Azure enthusiast, I decided to take a closer look at ML when Microsoft started to add Machine Learning components to Azure. Even then, I only got overwhelmed and confused by the enormous number of technologies and jargons surrounding it.

In another paper, Computational Thinking is Critical Thinking: Connecting University Discourse, Goals, and Learning Outcomes (2016) points out that abstraction is common to both computational and critical thinking. The author (Kules) essentially makes the case for bridging the two types of thinking. The clear definition of computational thinking quoted below is helpful. Similarly, the Venn diagram below demonstrates the overlap between creative and critical thinking, which programming just happens to inform. There is'abstraction & simplification' right in the center. I'll be the first to admit, "abstraction" might be impotent if you can't appreciate the complexity of it.

SHANGHAI-BASED online English learning platform Liulishuo said yesterday it has raised US$100 million from institutional investors and previous investors to fuel its future growth into artificial intelligence and tailor-made programs for English learners. China Media Capital and Wu Capital, as well as previous investors including TrustBridge, IDG Capital, GGV Capital, Cherubic Ventures and Hearst Ventures, have been announced as investors in the platform. Wang Yi, co-founder and chief executive officer of Liulishuo, said the company plans to hire more talent in the artificial intelligence field and to offer more AI-driven educational services besides its current AI-powered personalized interactive courses. "We hope to maintain our leading position in the artificial intelligence-backed online education field and to further enhance efficiency in English learning," he said, adding that they also hope to build an artificial intelligence learning research institution within two or three years. It will also provide AI-backed spoken English evaluating services for NASDAQ-listed TAL Education Group to integrate with TAL's current learning systems.

A clearer picture has emerged of what may have happened to the young members of Burundi's robotics team who vanished last week. The team's six teenage members disappeared after a robotics competition in Washington, D.C. -- but recent reports revealed their parents may have known of their plan not to return home. The principal of Iteletique High School, where two of the students were enrolled, said the teens told their parents of their plans in advance. The parents themselves have not yet made any public statements regarding the disappearances. "Talking with parents, they told us that once the kids arrived there, they told them they may not come back," the principal, Esperance Niyonzima, told VOA's Central Africa news service Thursday.

The multiverse of science fiction is populated by robots that are indistinguishable from humans. They are usually smarter, faster, and stronger than us. They seem capable of doing any job imaginable, from piloting a starship and battling alien invaders to taking out the trash and cooking a gourmet meal. The reality, of course, is far from fantasy. Aside from industrial settings, robots have yet to meet The Jetsons.

Five years from now, company leaders will be looking back and wishing they developed an artificial intelligence strategy sooner, according to one of the veterans of the field. Andrew Ng, the cofounder of Coursera and the former machine learning chief at Chinese tech powerhouse Baidu, said that he thinks Fortune 500 businesses will find the rise of AI similar to the rise of the internet. Some top CEOs bemoan how their businesses were late to the party when it came to competing on the internet, and Ng said that the same thing will be true when it comes to AI. In his view, businesses are best off hiring a leader with deep knowledge of the field who can help build up an organization's knowledge and capabilities in a centralized way. That chief AI officer, as he described it, would be charged with helping to bring expertise in the field to the rest of the a company.

Just as they have in manufacturing, defense, aerospace, transportation and dozens of other industries, robots and artificial intelligence are revolutionizing how humans teach and learn. Manifestations of robotic and AI teaching technology can already be seen in the educational sphere. For example, L2TOR is a project funded by the European Union aimed at developing an AI robot capable of helping preschoolers develop basic language skills. Futurist Brian David Johnson sees L2TOR as an early manifestation of a new wave of robotic tools that may become widespread in education. "These sentient tools will take over simple and social tasks that teachers and teaching aids provide today," he says.

Google today announced a new six-month program called Developers Launchpad Studio, created to support AI and machine learning startups around the world. Helpful perks to creators to be made available at the Developers Launchpad Studio include product validation support and introductions to AI investors, as well as feedback and advice from people like Google director of research Peter Norvig and Yossi Matias, head of Google's R&D Research Center in Israel. Participants will also receive $50,000 in financial support without the need to give Google equity, as well as product credits for services like Google Cloud. Companies ranging from small startups to larger post-series B companies that are using machine learning or AI to improve their products are encouraged to apply. The first class of applicants must submit a maximum 15-page pitch deck by August 31.

Posted By C. M. Rubin on Jun 20, 2017 "We need courageous cathedral builders! We also need to address traditional experts' biases clinging to their narrow domains, parents' old personal experiences biasing their views, and teachers' and administrators' lack of training and leadership, respectively." All around us we are witnessing disruptive automation that is changing lives and taking away the jobs many have relied on to make a living. According to a recent report by PwC, within 15 years, artificial intelligence will take over 38% of U.S. jobs. But will this trend continue even further, and to what extent does AI pose a threat to most of our jobs?