In episode six of season three we chat about the difference between frequentists and Bayesians, take a listener question about techniques for panel data, and have an interview with Katherine Heller of Duke.
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As the last in our series of blog posts on machine learning in research, we spoke to Dr Nathan Griffiths to find out more about machine learning in transport. Nathan is a Reader in the Department of Computer Science at the University of Warwick, whose research into the application of machine learning for autonomous vehicles (or “driverless cars”) has been supported by a Royal Society University Research Fellowship.
How can we create robots that can carry out important tasks in dangerous environments? Machine learning is supporting advances in the field of robotics. To find out more, we talked to Dr Rustam Stolkin, Royal Society Industry Fellow for Nuclear Robotics, Professor of Robotics at the University of Birmingham, and Director at A.R.M Robotics Ltd, about his work combining machine learning and robotics to create practical solutions to nuclear problems.
Imagine a future where self-driving cars, trains and buses are all seamlessly connected through an app, where traffic jams are a thing of the past and redundant car parks have been turned into green spaces. This could be the world we live in by 2030, says Cathis Elmsäter-Svärd, Chairwoman of Drive Sweden and a member of the Global Future Council on Mobility, in this interview.
Robotics undoubtedly has the potential to improve lives in the developing world. However, with limited budgets and expertise on the ground, putting this technology in place is no small task. Step forwards WeRobotics, a new Swiss/American NGO dedicated to meeting this goal through the creation of in-country ‘flying labs’. Co-founder Adam Klaptocz explains all.
In this interview, Dr. Yueh-Hsuan Weng invites Prof. Ronald C. Arkin, Executive Committee Member of IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems, to share his insights on roboethics, with a focus on its technical aspects, military and caregiver applications..
The UNEXMIN (Underwater Explorer for Flooded Mines) project is almost one year old. After a busy first year of work, UNEXMIN is on-schedule to deliver the first mechanical UX-1 prototype. Jussi Aaltonen, from TUT (Tampere University of Technology), leaders of WP1 – Robotic Functions Validations, talks about what has been done over the past year concerning his team’s work in UNEXMIN’s development scene.
Catalia Health is leading the surge in social robotics, with Mabu, their patient care management system. Catalia Health likes to be seen primarily as a health company that utilizes robots, rather than a robotics company. This focus on solving real world problems while shipping a product has seen Catalia attract both customers and investors, and recently close their Series A round.