Wndrco Closes $1 Billion Round of Funding for Mobile Video Platform (Report)

Jeffrey Katzenberg’s Wndco has raised $1billion in funding for its mobile video platform New TV, according to a report from CNN. Investors in the round included Disney, 21st Century Fox, Warner Bros, and Entertainment One.

A Wndrco spokesperson declined to comment on the situation.

According to the report, the service will be geared for mobile viewing and loaded with premium short-form content. To distribute the content, Katzenberg has looked to partner with tech and telecom companies like Facebook and Verizon, CNN sources said, but those companies do not appear to want to throw out their existing services for someone else’s. The report speculates that “New TV” may be a stand-alone service if a partner can’t be found.

The news comes at when more consumers are cutting the cord in favor of skinnier and more affordable OTT Packages, whether it be a vMPVD like SlingTV or a VOD service like Netflix. According to eMarketer, the number of cord-cutters— which the firm defines as adults that have canceled a pay-TV service and continued on without it—will climb 32.8 percent this year to 33.0 million.

With the world constantly looking for alternatives to traditional pay-TV, there is a lot of room for NewTV to grow, especially with $1billion dollar funding rounds. However, there is still much skepticism to as if short-form content is something consumers want to pay for. The push into short-form didn’t work well for Verizon when it launched go90 — a free service stacked with short-form content –which is expected to shut down at the end of this month.

Wndrco Closes $1 Billion Round of Funding for Mobile Video Platform (Report) was last modified: July 26th, 2018 by Matt Lopez

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Nvidia Creates AI That Can Significantly Reduce Noise and Erase Watermarks From Photos

Nvidia recently demonstrated an impressive AI that uses machine learning to « map corrupted observations to clean signals… [sometimes] without ever observing clean ones. » The AI is impressively powerful and can do many things, from reducing noise to removing watermarks.

Most such examples of these methods involve training a neural network using good and bad versions of an image. What makes this technique so impressive is that in certain circumstances, it doesn’t need good examples to train itself. The idea is an expansion of the concept of deviation-minimizing estimators, or M-estimators, which tell you how to estimate true data from from a set of unreliable data. By expanding this idea to the training of a neural network, the researchers were able to obviate the need for clean training examples, creating an AI that can, for example, learn how to reduce noise in a photograph by looking only at noisy photographs. While there are of course specific mathematical caveats, it’s a significant thing, as many applications often do not have clean examples to draw from, such as astrophotography. The scary part is that the AI can erase watermarks with ease, as you can see in the video above. Nevertheless, if the technology eventually reaches the consumer level, it could be a real boon for photographers when it comes to post-processing.

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