Media
RADAR Webinar - Press Association
The demand for quality local news, holding power to account and keeping audiences informed and engaged, is higher than ever. RADAR is a new service which harnesses the power of technology to deliver incisive, fact-based news stories to local media across the UK and Ireland. It brings together PA, the national news agency with over 150 years' experience in supplying quality content, and Urbs Media, a tech driven start up using a combination of reporters and automation to mass localise news. Reports And Data and Robots (RADAR) is a global first in successfully combining humans and machine to scale up local news production across core local news pillars such as; health, education, crime, transport, housing and environment. RADAR is moving towards a full market launch and is expected to be able to create 30,000 localised stories each month. Register for this webinar where PA's Editor-in-Chief, Pete Clifton and RADAR's Alan Renwick will outline the details of the service; how the technology works, the content topics, the assets we'll be producing and the ways in which news outlets can access and use the service.
Can AI win the war against fake news?
It may have been the first bit of fake news in the history of the Internet: in 1984, someone posted on Usenet that the Soviet Union was joining the network. It was a harmless April's Fools Day prank, a far cry from today's weaponized disinformation campaigns and unscrupulous fabrications designed to turn a quick profit. In 2017, misleading and maliciously false online content is so prolific that we humans have little hope of digging ourselves out of the mire. Instead, it looks increasingly likely that the machines will have to save us. One algorithm meant to shine a light in the darkness is AdVerif.ai,
Human beings could achieve immortality by 2050
Old age could soon be old news, according to a leading futurologist who claims people born after 1970 could live forever. He predicts that by the year 2050, humans could outlive the constraints of the physical body. Genetic engineering could be used to extend the body's life expectancy, by reducing or reversing the ageing of cells. Advances in AI could lead to android bodies for humans to live in after their own flesh and blood frames have ceased to function. And virtual reality worlds could be created for people to upload their consciousness into once their bodies have failed. Old age could soon be old news, according to a leading futurologist who claims people born after 1970 could live forever.
The anxious euphoria of Davos
One of the themes that dominated this year's forum was artificial intelligence. For Sundar Pichai, the head of Google, "artificial intelligence (AI) will save us, not destroy us. AI is probably the most important thing humanity has ever worked on. I think of it as something more profound than electricity or fire.".
[P] CNN learning to play snake using RL • r/MachineLearning
All is open source, though not "published" yet so excuse me if the repository is a bit hard to navigate / unclear. I've been building a Unity-esque 2D engine with pygame, which should be easy to plug in with OpenAI's gym. Goal here isn't to build the most optimal environments per se, but a way to implement games that are human and AI playable. Hopefully I'll get to release a slightly more convenient setup soon, with each (sub)project separated into their own repo:)
"[Discussion]" Tips for Writing Papers for Academic Audience • r/MachineLearning
I'm writing my first paper, which I am looking to publish in an academic journal. I'm a little intimidated by some of the papers that I was reading in the journals that I am looking to submit to. While the quality in the papers is definitely great, I feel there's a lot just with regards to the authors' skill in presentation. In addition to that, I feel like the journal papers seem to write well for the academic audience. I don't have a natural understanding of the nuances of this audience. Personally, I feel like I have a more down-to-earth personality, so if I was implementing a 20-layer network, I would say I am implementing a deep learning network, whereas in one of the academic papers, someone may say they are implementing a 20-layer encoder-decoder convolutional network.