Today's leading minds talk AI with host Byron Reese On Episode 108 of Voices in AI, Byron and Kirk Borne discuss the intersection between human nature and artificial intelligence. Listen to this episode or read the full transcript at www.VoicesinAI.com Byron Reese: This is Voices in AI brought to you by GigaOm, and I'm Byron Reese. Today my guest is Kirk Borne. He is Principal Data Scientist and executive advisor at Booz Allen Hamilton.

In the previous project, we talked about implementing Lane Line Detection and we observed there are some limitations in adverse light conditions. Also, we know that the algorithm does not work correctly when the road would turn left or right. In this project, we are going to eliminate those restrictions by using new algorithms. So let's talk about some essential concepts and instruments. At first, for making our implementation more realistic, let's talk about a technique which is called Camera Calibration.

Josh Swamidass is the Washington University computational biologist and intelligent design critic who debated with biochemist Michael Behe last week at Texas A&M. Their exchange is now up on YouTube. Jonathan Witt reported on the contents here. Dr. Swamidass then headed to Seattle where he spoke last night at the University of Washington on "Human Identity and the Meaning of Artificial Intelligence: A Conversation with a Secular Humanist and a Scientist Christian." It was good to see Josh in the flesh.

So I think that those three areas that separates us from far from the crowd. The first one is about a model of safety. We are we published a paper two years ago about how to formalize a common sense of human driving how to define what a dangerous situation is in the context of decision making on merging into traffic . And since then we have been working with regulatory bodies to standardize this model . We are the only company that is really transparent about its safety safety model.

He also explains where he draws inspiration from in his research, and why robotics has yet to meet science fiction. Vijay Kumar is the Nemirovsky Family Dean of Penn Engineering with appointments in the Departments of Mechanical Engineering and Applied Mechanics, Computer and Information Science, and Electrical and Systems Engineering at the University of Pennsylvania. Kumar's group works on creating autonomous ground and aerial robots, designing bio-inspired algorithms for collective behaviors, and on robot swarms. They have won many best paper awards at conferences, and group alumni are leaders in teaching, research, business and entrepreneurship. Kumar is a fellow of ASME and IEEE and a member of the National Academy of Engineering.

Stuart Russell is a distinguished artificial intelligence researcher, a Professor of Computer Science at the University of California, Berkeley, an Adjunct Professor of Neurological Surgery at the University of California, San Francisco, and leads the Center for Human-Compatible Artificial Intelligence at UC Berkeley. Along with Peter Norvig, Stuart is the author of Artificial Intelligence: A Modern Approach, the most widely used textbook on artificial intelligence. In his most recent book, Human Compatible: AI and the Problem of Control, Stuart proposes a fundamentally new approach to developing AI. In this interview, Stuart warns that AI is reshaping society in unintended ways. For example, social media content selection algorithms that choose what individuals watch and read do not even know that human beings exist. As AI becomes more capable, he suggests that we are going to see bigger failures unless we change the way we think about AI altogether. Stuart argues that to ensure AI is provably beneficial for human beings, we must design machines to be inherently uncertain about human preferences. This way, we can ensure they are humble, altruistic, and committed to pursuing our objectives even as they set their own goals. We also discuss why AI needs regulation similar to civil engineering and medicine, the impact AI is going to make over the next decade, autonomous vehicles, and a variety of other topics.

Anyone who uses the cut, copy and paste commands on their computer or mobile device has Larry Tesler to thank for making them so simple and easy to use. Tesler, who has died aged 74, began his work on cut, copy and paste in 1973, when he was hired by Xerox's Palo Alto Research Center (Parc) in California. Among other things he worked with a fellow computer scientist, Tim Mott, on the development of Gypsy, a "modeless" word processor. At the time most software had modes: for example, you might press I to enter the insert mode, or R for the replace mode. But Tesler's research showed that non-expert users found modes confusing – and so he began to fight against them.

My father, David Aspinall, who has died aged 86, was one of a small group of researchers who founded the field of computer science in the UK. As an engineering research student he was involved in building the Manchester University Atlas computer which, when it was switched on in 1962, was the fastest in the world. In 1970, David moved to University College Swansea to become professor of electrical engineering and create a new course, a BSc in computer technology, based on the model designed by his boss Tom Kilburn whose computer science department at Manchester University was the first of its kind in the UK. These people were the pioneers of the new academic and educational field of "computer science". David was born in Cleveleys, Lancashire, the son of Hilda (nee Whittle), who had worked in the weaving sheds of Blackburn before her marriage, and William Aspinall, a civil servant.

A Generative Adversarial Network for AI-Aided Chair Design Researchers present a deep neural network for improving human design of chairs which consists of an image synthesis module and a super-resolution module. They select one of the candidates as a design prototype and create a real-life chair based on it. According to the researcher team, this is the first physical chair created with the help of deep neural networks, which bridges the gap between AI and design. This is the largest NLP model ever trained, with 17 billion parameters. T-NLG has achieved SOTA performance on mainstream NLP tasks.

We know machines and artificial intelligence (AI) can be many things, but can they ever really be creative? When I interviewed Professor Marcus du Sautoy, the author of The Creativity Code, he shared that the role of AI is a "kind of catalyst to push our human creativity." It's the machine and human collaboration that produces exciting results--novel approaches and combinations that likely wouldn't develop if either were working alone. Can Machines And Artificial Intelligence Be Creative? Instead of thinking about AI as replacing human creativity, it's beneficial to examine ways that AI can be used as a tool to augment human creativity.