If Netflix's decisions on marketing its hundreds of original shows seem highly calculated... that's probably because they were. Netflix has outlined how it uses AI to market shows and predict their success in ways that conventional box office numbers and Nielsen ratings likely couldn't match. Effectively, it comes down to finding connections and determining the likely audience sizes. The method relies on transfer learning, where the the parameters learned from a "source task" improve the performance of a "target task." In this case, the source tasks are simple: what titles are comparable to a Netflix original, and what kind of viewership can the service expect?

Sometimes, like a total eclipse, my two great passions--technology and reality TV--become one. It happened in November 2017, when, on the Wednesday before Thanksgiving, I cajoled then-Future Tense contributor Jacob Brogan into writing about the previous night's Teen Mom 2 episode. It grappled with a critical question: Is it OK to shoot down a drone flying above private property? The segment in question begins as (former) teen mom Jenelle prepares for her wedding to David, a very cool and normal dude who we will return to in a moment. David, stalking the property like an ornery bison, calls Jenelle, informing her that "some girls" were attempting to take pictures of the event before it began.

This isn't the first time that we must question whether "seeing" is in fact "believing" Earlier this week the YouTube channel Shamook highlighted the latest Deepfake technology in which scenes involving two notable characters in Rogue One: A Star Wars Story were greatly enhanced. This was the latest such use of Deepfakes in pop culture. What was impressive about this most recent use of the technology is that it made the character of Governor Tarkin seem more lifelike and more closely resembled Peter Cushing, the late actor who played the role originally in the 1977 film Star Wars. The same technology was previously employed earlier this year on the YouTube channel to "de-age" Robert De Niro and the results were far than what was actually seen in the Netflix original film The Irishman. Both of the "original" versions seem far more cartoony and fall into that "uncanny valley" of not being quite real.

In this episode of the Data Exchange I speak with Xinyi Zhou, a graduate student in Computer and Information Science at Syracuse University. Xinyi and her advisor (Reza Zafarani) recently wrote a comprehensive survey paper entitled "A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities". They set out to organize the many different methods and perspectives used to detect fake news. Their paper is a great resource for anyone wanting to understand the strengths and limitations of various state-of-the-art techniques, and a feel for where the research community might be headed in the near future. We first discussed good working definitions for "fake news".

Two years ago, the Google News Initiative partnered with the London School of Economics and Political Science to launch JournalismAI, a global effort to foster media literacy in newsrooms through research, training and experimentation. Since then, more than 62 thousand journalists have taken Introduction to Machine Learning, an online course provided in 17 languages in partnership with Belgian broadcaster VRT. More than 4,000 people have downloaded the JournalismAI report, which argued that "robots are not going to take over journalism" and that media organizations are keen to collaborate with one another and with technology companies. And over 20 media organizations including La Nación, Reuters, the South China Morning Post and The Washington Post have joined Collab, a global partnership to experiment with AI. To mark this anniversary, together with the London School of Economics, we are hosting a week-long online event to bring together international academics, publishers and practitioners.

Some people's lives are like horror movies. It's strange that, in an age that can create virtual reality, self-driving cars and intelligent machines, the world's third-largest economy can't solve the problem of human misery. More and more Japanese women seem to feel it is. Female suicide is sharply rising. National Police Agency statistics tell the tale, as far as numbers can tell it -- 651 women are known to have taken their own lives that month, up from 400-500 a month typically.

Emily, your lamentation that we don't take the time to discuss big, knotty shows in detail anymore got me thinking. And what I think is … I am to blame? I'm not egomaniacal enough to think I alone am to blame. Streaming platforms that drop entire seasons on as at once might be more responsible, but I too play my tiny part in this state of affairs. The first way is: I like it.

"The tests demonstrated our success in applying artificial intelligence algorithms to'teach' the aircraft's brain to understand what is required of it," says …

The United States' Special Operations Command is currently playing a critical role advancing the employment of AI and machine learning in the fight …

It also requires computer algorithms and artificial intelligence. The United States' Special Operations Command is currently playing a critical role …