The person who uploads a particular video to, say, YouTube doesn't even need much of a following in order for the video to garner enough attention to be shared over and over and attract people to leave so many comments (both negative and positive) that one person cannot simply sift through them fast enough. Last May, this happened to the Gay and Lesbian Alliance Against Defamation, also known as GLAAD. The organization posted a video of actress Debra Messing accepting GLAAD's Excellence in Media Award for her work in helping push an agenda for equality in the film and television industry. In her speech, Messing pushed for the Trump administration to "do right" by the LGBTQ community by removing certain staff members and focusing on laws that reflect equality. After posting the video on its YouTube channel, GLAAD received an outpouring of comments from people who had something negative to say about Messing and her speech.

Facebook will pay publishers up front to create the content, according to a person familiar with the program, who added that questions related to advertising on the section have not been answered yet. Some publishers are wary of the new program, given Facebook's track record of introducing new initiatives with news organizations only to later cut back financial support. For example, in 2016 Facebook signed video creators, including CNN, The Wall Street Journal and the New York Times, to 12-month deals collectively worth at least $50 million to create live video. Facebook didn't renew many of those deals after they expired, leaving publishers without funding for content producers hired to produce live video on Facebook. That said, given the prospects of exposure on the world's biggest social network and potential revenue from lucrative video ad sales, some news publishers are still considering participating in the Facebook Watch news initiative--under the right circumstances.

A new Alexa skill has popped up called DeepMusic that enables you to listen to songs generated by artificial intelligence, as spotted by Music Ally. Per the official page on Amazon, the songs generated by DeepMusic are composed entirely from AI. However, it also says that it "us[es] a collection of audio samples and a deep recurrent neural network," suggesting that it either a) has samples of individual notes from instruments or b) splices together or layers snippets of sampled audio the algorithm believes will work well together. DeepMusic says that the music it creates has "no post-production editing by a human." AI was also used to create the DeepMusic artwork displayed on the Echo Show and Echo Spot speakers.

Welcome to Cheat Sheet, our brief breakdown-style reviews of festival films, VR previews, and other special event releases. This review comes from the 2018 SXSW Interactive Festival. For the documentary More Human Than Human, which premiered at SXSW 2018, directors Tommy Pallotta and Femke Wolting started with a hooky premise: to explore the current state of artificial intelligence, Pallotta (producer of Richard Linklater's Waking Life) was going to try to replace himself with a robot. The directors set a robotics lab to work on the project, building a "camerabot" that was meant to scan faces, recognize emotions, train its camera on its subjects, generate questions, and interview them. As the dev team works on that project, Pallotta -- a frequent onscreen presence, as interviewer and the intended final interviewee -- fills the time by talking to other programmers, roboticists, and futurists about their AI projects or research, trying to build a sense of the state of AI art.

A message concealed in one of Richard's old puzzle-boxes grants Lara access to her father's archive of materials on the Himiko project. Tasked with finding out how he met his end, she jets off to Hong Kong, where she befriends a drunk, rifle-toting boatman, Lu Ren (Daniel Wu), who eventually sobers up and agrees to steer her through tempestuous waters to Yamatai. This may be as good a place as any to note that "Tomb Raider" was directed by Norway's Roar Uthaug, who previously directed the 2016 disaster flick "The Wave," and who once again proves a peerless choreographer of massive walls of computer-generated water.

Barbara started by introducing machine learning (ML), gave a brief overview of R and then discussed three examples; classifying hand written digits, estimating values in a socio-economic dataset and clustering crimes in Chicago. ML is statistics in steroids. ML uses data to find that pattern then uses that pattern (model) to predict results from similar data. Barbra uses the example of classifying film genres into either action or romance based on the number of kicks and kisses. Barbara described supervised and unsupervised. Unsupervised is the "wild, wild west" we can't train the model and it is much more difficult to understand how effective these are. Back to supervised learning, it's important to choose good predicting factors – in the movie example perhaps the title, actors, script may have been better predictors that the number of kicks and kisses. Then you must choose the algorithm and then tune it and finally make it useful and visible and get it into production - it's a hard job especially when data scientists and software developer seem to be different tribes.

CableLabs just released a cool short film called The Near Future: A Better Place that explores how emerging technologies in healthcare will transform our daily lives. A substantial percentage of the population worldwide is over the age of 60, and it will dramatically increase in the next two decades. This really underscores the importance of healthcare advancements, and connectivity is the underlying component that will power the emerging technologies that can transform our daily lives, such as IoT, telemedicine, intelligent agents and new sensors. For example, Cookie – the little robot AI Agent in the film is an in-home companion that provides social interaction, around the clock monitoring, as well as a direct interface with the complex system of care at the hospital. With this short film, CableLabs wants to inspire you and the entire tech and healthcare industry to help make this vision a reality in the near future.

Almost a third (32%) of consumers surveyed globally by PwC plan to buy an AI device including robots or automated assistants, with retailers watching closely as'voice commerce' develops in the home. The findings are published today in PwC's Global Consumer Insights survey, which assesses the shopping behaviour, habits and expectations of over 22,000 consumers in 27 countries. The study reports that 10% of respondents already own artificial intelligence (AI) devices, such as robots and automated personal assistants like Amazon Echo or Google Home, and 32% said they plan to buy one. Both consumer and retailer habits and offerings still need time to adapt however, to make the most of the new voice commerce channel. Interest in the devices is strongest amongst consumers in emerging economies including China, Vietnam, Indonesia and Thailand.

This is a continuation of the three part series on machine learning for product managers. The first note focused on what problems are best suited for application of machine learning techniques. As I had mentioned in Part I, the core skill sets required of a PM do not change whether you work in a machine learning driven solution space or not. Product managers typically use five core skills -- customer empathy/design chops, communication, collaboration, business strategy and technical understanding. Working on ML will continue to leverage these skills.

Amazon's Alexa is becoming less hospitable to people who prefer to buy music instead of just signing up for a music subscription service such as Spotify. Until recently, Amazon Music Storage was the best way to stream your personal music collection onto Alexa devices--provided it was encoded as MP3 files. But in December, Amazon stopped supporting new uploads for the free service; it stopped accepting paid subscriptions a month later. In January 2019, Amazon will shut down Music Storage entirely, rendering your MP3 collection inaccessible on Echo devices unless you purchased the songs directly through Amazon's digital store. To play your own MP3s (or music encoded in other formats, such as FLAC) on the Echo or other Alexa devices, you can still use Plex or My Media Server for Alexa, both of which allow you to stream songs that you've stored on another device.