2017-11
Gaming Machine Learning
Over the last few years, the quest to build fully autonomous vehicles has shifted into high gear. Yet, despite huge advances in both the sensors and artificial intelligence (AI) required to operate these cars, one thing has so far proved elusive: developing algorithms that can accurately and consistently identify objects, movements, and road conditions. As Mathew Monfort, a postdoctoral associate and researcher at the Massachusetts Institute of Technology (MIT) puts it: "An autonomous vehicle must actually function in the real world. However, it's extremely difficult and expensive to drive actual cars around to collect all the data necessary to make the technology completely reliable and safe." All of this is leading researchers down a different path: the use of game simulations and machine learning to build better algorithms and smarter vehicles.
New ITU Focus Group to study Machine Learning in future networks including 5G OpenGovAsia
The International Telecommunications Union (ITU), the United Nations specialised agency for information and communication technologies (ICTs), has launched a new ITU Focus Group to establish a basis for ITU standardisation to assist machine learning (ML) in bringing more automation and intelligence to ICT network design and management.
"OK Google!" Researched for Medical Conversations
Medical transcription is often seen as one of the more mundane tasks that need to be done in the doctor's office. Yet, it's vitally important for making sure that medical records are accurate, and that all of the physician's observations, orders, and conversations with patients is properly documented.
Drone Pilot Arrested After Dropping Leaflets Over NFL Games
Federal and local laws prohibit flying drones near football games, and authorities are examining additional ways to prevent the unmanned aircraft from hovering over crowds of tens of thousands of people after the flights Sunday, Santa Clara police Lt. Dan Moreno said. He declined to discuss the security measures being considered.
Can A.I. Be Taught to Explain Itself?
In September, Michal Kosinski published a study that he feared might end his career. The Economist broke the news first, giving it a self-consciously anodyne title: "Advances in A.I. Are Used to Spot Signs of Sexuality." But the headlines quickly grew more alarmed. By the next day, the Human Rights Campaign and Glaad, formerly known as the Gay and Lesbian Alliance Against Defamation, had labeled Kosinski's work "dangerous" and "junk science." In the next week, the tech-news site The Verge had run an article that, while carefully reported, was nonetheless topped with a scorching headline: "The Invention of A.I. 'Gaydar' Could Be the Start of Something Much Worse."