Video: How Will Machine Learning Impact the Media Supply Chain?
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Read the complete transcript of this clip:
Leonidas Kantothanassis: What does machine learning apply to? Surprisingly, pretty much everything in the media workflow, in the media supply chain. Things that you might not expect, like say compression. Let’s say you have a show, and machine learning can actually automatically detect how dynamic the views are and adjust your transcoding so that you will allocate more or fewer bits or frame rate. This can actually help you not only produce a better video, but also a video that is cheaper to transmit in the end. It would actually give the best experience at the minimum number of bits.
You can also use it for closed caption creation. Often for regulatory reasons this has to be done, and doing it manually is a very expensive process. With machine learning you can actually do it in real time on-the-fly, and translate it to over a 100 languages at the same time. That is a great capability that couldn't be done without it.
Contextual ads, discovery recommendations, video insights, there are all these areas that machine learning can actually make easier and make the end-user experience can feel much more personalized to the consumer.
What is available today? There are a number of machine learning APIs that are avaible already in Google Cloud. Natural language, speech, translation, vision, and video intelligence are already some of the technologies that exist and have APIs that you can use. Nuances are coming online all the time. Watch this space for announcements. We expect to be very active in this space and be announcing new APIs and capabilities all the time.
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