Tag Archives: Artificial Intelligence

Five ways artificial intelligence can help space exploration

Deep Bandivadekar is a PhD student at the Aerospace Centre of Excellence, University of Strathclyde and does research work as part of the Intelligent Computational Engineering Laboratory (ICE-Lab). His research interests are Computational Fluid Dynamics (CFD), Thermodynamics, Hypersonics, Artificial Intelligence, Design Optimisation, Global and Multi-objective Optimisation.

Audrey Berquand is a PhD candidate in Mechanical and Aerospace Engineering, University of Strathclyde. Her research question asks – “Can all the data and lessons learned harvested online, collected from previous current and future studies, be reused and enhanced with computational intelligence methods to advance current concurrent engineering design processes and decision making at the early phases of space missions design?”

We’re teaching robots to evolve autonomously – so they can adapt to life alone on distant planets

Professor Emma Hart is Chair in Natural Computation, Edinburgh Napier University. She is active world-wide in the field of Evolutionary Computation, an Editor-in-Chief of Evolutionary Computation (MIT Press) from January 2016 and an elected member of the ACM SIGEVO Executive Board. She is also a member of the UK Operations Research Society Research Panel.

Flailing About – and Having Compassion on Ourselves – as We Stand on the Verge of a New Renaissance

The lead author’s experience with AICAN and other art and artificial intelligence projects at Rutgers University has inspired the thought that the art world finds itself in a period of discovery and experimentation similar to that leading up to the original Renaissance. As artists navigate this new territory, there is hence much “flailing about”, but it can nonetheless be argued that there will soon enough emerge one or more techno/new media art schools of evident confidence and inspiration. The authors conclude by venturing an informed opinion as to a preferred course for future creative engagement with the emerging machine intelligence.

Why AI can’t ever reach its full potential without a physical body

Mark Lee is Emeritus Professor in Computer Science, Aberystwyth University. “I have degrees in Electrical Engineering and Psychology and have worked in AI, robotics and CS for 40 years. I am a fellow of the IET and of the Learned Society of Wales. My research explores how robots might learn about the world in the same way that infants build up their understanding in the first few years. This approach (known as Developmental Robotics) contrasts with the Big Data and Deep Learning methods of modern Artificial Intelligence. My recent book, “HOW TO GROW A ROBOT: DEVELOPING HUMAN-FRIENDLY, SOCIAL AI” (MIT Press, 2020) explains these ideas, and their consequences, in detail.”

It’s not easy to give a robot a sense of touch

Ajay Pandey is a Senior Lecturer in Robotics and Autonomous Systems at the School of Electrical Engineering and Computer Science. He completed his PhD in Physics on Organic Optoelectronics with mention tres honourable from University of Angers, France. His research interest has the interdisciplinary mix of Photonics, Chemical Physics, Molecular Electronics, Neuroscience and Robotics. He leads an interdisciplinary research group at QUT that specialises in technological implementation of advanced materials for applications in Neuroscience, Intelligent Bionics, Medical Robotics, Soft Robotics, Energy conversion and Night Vision.

Jonathan Roberts is Professor in Robotics at Queensland University of Technology (QUT). His main research interest is in the area of Field Robotics and in particular making machines operate autonomously in unstructured environments. Jonathan is the co-inventor, and current head judge of the UAV Challenge Outback Rescue, an international flying robot competition in which teams search for a lost bushwalker using autonomous robotic aircraft. In 2013 Jonathan made international news by being the first person to 3D map the interior of the Leaning Tower of Pisa using his team’s Zebedee 3D laser scanning mobile mapping system. He continues to have an interest in the use of robotics technology for the use in documenting and protecting important cultural heritage sites.

From Computational Creativity to Creative AI and Back Again

Simon Colton is a British computer scientist, currently working as Professor of Computational Creativity in the Game AI Research Group at Queen Mary University of London, UK and in the Sensilab at Monash University, Australia. He previously had an appointment at Falmouth University, UK and led the Computational Creativity Research Groups at Goldsmiths, University of London and at Imperial College, London in the positions of Professor and Reader, respectively. Simon is the driving force behind thepaintingfool.com, an artificial intelligence that he hopes will one day be accepted as an artist in its own right.

Neural Zoo

Sofia Crespo’s work consists of different projects working with artificial intelligence, computed image recognition, and neural networks. Her project, Neural Zoo, explores how creativity combines known elements in a specific way in order to create something entirely new. In the process of generating new creatures, that don’t exist yet, she offers a perspective on how similar human creativity works. The creator, in this case, would be the algorithm itself, but with a human artist as its muse.

Art and Generative Systems

Gene Kogan is an artist, programmer and leading educator in the field of creative AI – who is developing the world’s first decentralized autonomous artist. He is a collaborator within numerous open-source software projects, and gives workshops and lectures on topics at the intersection of code and art.

Meet AICAN, a machine that operates as an autonomous artist

Ahmed Elgammal is Professor at the Department of Computer Science, Rutgers University. Director of the Art & AI Lab. Executive Council Faculty at the Center for Cognitive Science at Rutgers University. His research focusses on Computer Vision, Visual Learning, Data Science in Digital Humanities, and Human motion analysis. His research on Art & AI received wide international media attention, including many reports on the Washington Post, New York Times, NBC News, the Times, the Daily Telegraph, Science News, and many others.