Artificial Intelligence (AI) is the mantra of the current era. The phrase is intoned by technologists, academicians, journalists and…

In early 2017, we published the German AI Landscape, and later in 2017, we created the European AI Landscape. We determined that London, Paris, and Berlin were strong individual hubs for Artificial…

In the natural world, intelligence takes many forms. It could be a bat using echolocation to expertly navigate in the dark, or an octopus quickly adapting its behavior to survive in the deep ocean. Likewise, in the computer science world, multiple forms of artificial intelligence are emerging - different networks each trained to excel in a different task. And as will be presented today at the 25th annual meeting of the Cognitive Neuroscience Society (CNS), cognitive neuroscientists increasingly are using those emerging artificial networks to enhance their understanding of one of the most elusive intelligence systems, the human brain.

Columbia Business School data scientist Professor Daniel Guetta , Director of the Business Analytics Initiative at Columbia Business School and Columbia Engineering, has published a case study about Evisort , an Artificial Intelligence (AI)-enhanced document management and data analytics solution for contracts developed by Harvard Law and MIT researchers. Guetta begins teaching the Evisort case study today in a new Business Analytics MBA class, the latest in Columbia’s growing data- and analytics-focused offerings for MBAs. The case study, entitled: “ Evisort: An A.I.-Powered Start-up Uses Text Mining to Become Google for Contracts ,” will be joined by a technical case study counterpart in the near future.

Technavio analysts forecast the global artificial intelligence in the aviation market to grow at a CAGR of nearly 38% during the forecast period, according to their latest market research report.

Should we be scared of artificial intelligence (AI)? Some notable individuals such as legendary physicist Stephen Hawking and Tesla and SpaceX leader and innovator Elon Musk suggest AI could potentially be very dangerous; Musk at one point was comparing AI to the dangers of the dictator of North Kor

In a new book published this week titled Architects of Intelligence, writer and futurist Martin Ford interviewed 23 of the most prominent men and women who are working in AI today, including DeepMind CEO Demis Hassabis, Google AI Chief Jeff Dean, and Stanford AI director Fei-Fei Li. In an informal survey, Ford asked each of them to guess by which year there will be at least a 50 percent chance of AGI being built. Short answer: maybe within our lifetimes, but don’t hold out.

Surgery filmed in 360° and live-streamed to remote doctors could already be happening in a hospital near you. The healthcare industry should be using Artificial Intelligence (AI) to a far greater degree than at present, but progress has been painfully slow. The same factors that make the healthcare system so attractive to AI developers – fragmented or non-existent data repositories, outdated computer systems and doctor shortages – are the same things that have stopped AI from providing the gains that should be created. The healthcare sector also presents unique obstacles for AI: data must flow freely through AI systems to achieve real results, but extracting data from handwritten patient files or PDFs is cumbersome for us, and difficult for AI. Despite technical and operational challenges, new research suggests that the arrival of the tech giants into the industry may provide the data and the capital required to digitize this fairly untapped market.

Intellectual Property (IP) refers to exclusive rights associated to creations of the mind. These rights allow creators, or owners, of patents…

by Larry Pitt