In recognition of the fact that their obituary pages had been dominated by white men, in 2018 the New York Times published an obituary of the Countess Ada Lovelace. Alongside Grace Hopper and Katherine Johnson, Lovelace has become an icon for women in technology. So much so that the second Tuesday in October is recognised internationally as Ada Lovelace Day. Lovelace was from a wealthy background; her father was the poet Lord Byron and her mother, Anne Isabella Milbanke, the "princess of parallelograms", was a keen mathematician and social reformer. Social scientists of today would describe Lovelace as having high "science capital" – her well-connected parents meant her mentors and advisers were members of the British scientific elite, including the polymaths Mary Somerville and Charles Babbage.

Restricting the number of potential readers is unfortunate because an interdisciplinary view of the world around us must be developed. This book should have been written to show a scientist with a good mathematics background how to do modeling and simulation. Scientific research needs more people trained in system concepts, people trained to understand and apply the Weltanschauung of system theory. Indeed, the recent recommendation for science education that came out of the Science for All Americans study, sponsored by the American Association for the Advancement of Science, emphasized an interdisciplinary approach to scientific concepts. By limiting the technical accessibility of this book, the author has not helped us address the need for training scientists in the use of interdisciplinary tools in scientific research.

The three competitions--(1) AAAI Mobile Robot, (2) AUVS Unmanned Ground Robotics, and (3) IJCAI RoboCup--were used in different years for an introductory undergraduate robotics course, an advanced graduate robotics course, and an undergraduate practicum course. Based on these experiences, a strategy is presented for incorporating competitions into courses in such a way as to foster intellectual maturation as well as learn lessons in organizing courses and fielding teams. The article also provides a classification of the major robot competitions and discusses the relative merits of each for educational projects, including the expected course level of computer science students, equipment needed, and costs. The sponsorship of such competitions ranges from local clubs of enthusiasts to large professional organizations, such as the American Association for Artificial Intelligence (AAAI), which sponsors the annual AAAI Mobile Robot Competition and Exhibition as part of its annual ...

It included an invited talk, paper presentations, model AI assignments, a teaching and mentoring workshop, a best educational video award, and a robotics track. The symposium was established in response to growing community interest in sharing best practices for (1) how to teach AI and (2) how AI can serve as a motivating problem for teaching concepts in other areas of computer science, especially in introductory computer science courses. EAAI encourages the sharing of innovative educational approaches that convey or leverage AI and its many subfields, including robotics, machine learning, natural language, and computer vision. EAAI follows the successful 2008 Spring Symposium on "Using AI to Motivate Greater Participation in Computer Science" and the 2008 AAAI AI Education Colloquium. Fifty-five attendees formally registered for the event, but many other AAAI attendees also visited one or more EAAI events.

Column n The Educational Advances in Artificial Intelligence column discusses and shares innovative educational approaches that teach or leverage AI and its many subfields at all levels of education (K-12, undergraduate, and graduate levels). Have you ever been surprised by poor class performance on a midterm question, and wondered why you were met with silence each time you asked "Any questions?" during the lecture on that topic? Do your students sometimes feel like they understood everything that was said in lecture, only to go home, start the homework, and immediately get stuck? Do you find that you only really learn something when you have to explain it to others? Peer instruction is an active learning pedagogy that addresses these challenges and opportunities.

Since we will be using scientific computing and machine learning packages at some point, I suggest that you install Anaconda. This actually is a reflection of the field of machine learning, since much of what data scientists do involves using machine learning algorithms to varying degrees. Gaining an intimate understanding of machine learning algorithms is beyond the scope of this article, and generally requires substantial amounts of time investment in a more academic setting, or via intense self-study at the very least. For example, when you come across an exercise implementing a regression model below, read the appropriate regression section of Ng's notes and/or view Mitchell's regression videos at that time.

Washington, D.C. - IBM, a pioneer in the advancement of artificial intelligence, today welcomed the release of a White House report on the future and promise of this exciting technology: "We commend the Administration, and the Office of Science and Technology Policy (OSTP) in particular, for launching an open and inclusive dialogue that helped shape today's report. The document recognizes what IBM has believed all along, that artificial intelligence (AI), or cognitive computing systems like IBM Watson, will jump start economic opportunity and help solve some of humanity's biggest challenges. Embedding ethical training into computer science education, as the report recommends, is a positive way to prepare the next generation of technology experts to appropriately guide the advancement of AI systems. Cybersecurity is one area in particular where IBM agrees that AI can be a true game-changer, and one where we are actively preparing IBM Watson to make a real and tangible difference in the push to better defend America's digital networks.

I learned about entropy as part of my undergraduate Physics education but it turns out that the concept of entropy turns up in many fields including linguistics, themodynamics, information theory, chemistry and artificial intelligence. As part of Sheffield's Open Data Science Initiative, computer scientist, Neil Lawrence, has teamed up with linguist, Dagmar Divjak, to organise a cross-faculty discussion meeting on the subject of entropy. For more details on the day's events, and to register, see http://opendsi.cc/ed2016/program I wasted a little time producing the above logo for the event using Mathematica. You should call it entropy, for two reasons.

The three competitions -- (1) AAAI Mobile Robot, (2) AUVS Unmanned Ground Robotics, and (3) IJCAI RoboCup -- were used in different years for an introductory undergraduate robotics course, an advanced graduate robotics course, and an undergraduate practicum course. Based on these experiences, a strategy is presented for incorporating competitions into courses in such a way as to foster intellectual maturation as well as learn lessons in organizing courses and fielding teams. The article also provides a classification of the major robot competitions and discusses the relative merits of each for educational projects, including the expected course level of computer science students, equipment needed, and costs.