Netflix Tech
DECEMBER 10, 2020
Our catalog of thousands of films and series caters to 195M+ members in over 190 countries who span a broad and diverse range of tastes. The commissioning of a series or film, which we refer to as a title , is a creative decision. as is the uncertainty of the outcome (it is difficult to predict which shows or films will become hits).
Altexsoft
MAY 12, 2022
Today, we have AI and machine learning to extract insights, inaudible to human beings, from speech, voices, snoring, music, industrial and traffic noise, and other types of acoustic signals. At the same time, keep in mind that neither of those and other audio files can be fed directly to machine learning models.
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CIO
OCTOBER 13, 2023
A recent survey of senior IT professionals from Foundry found that 57% of IT organizations have identified several areas for gen AI use cases, 25% have started pilot programs, and 41% are engaged in training and upskilling employees on gen AI.
CIO
DECEMBER 13, 2023
The evolution of AI and the use of structured and unstructured data When discriminative AI rose to prominence in sectors such as banking, healthcare, retail, and manufacturing, it was primarily trained on and used to analyze, classify, or make predictions about unstructured data. What’s hiding in your unstructured data?
Altexsoft
JULY 27, 2021
And what does machine learning have to do with it? In this article, we’re taking you down the road of machine learning-based personalization. You’ll learn about the types of recommender systems, their differences, strengths, weaknesses, and real-life examples. Content-based filtering example. Model-based.
Netflix Tech
NOVEMBER 6, 2023
You don’t know if that shot exists or where it is in the film, and you have to look for it it by scrubbing through the whole film. Exploding cars — The Gray Man (2022) Or suppose it’s Christmas, and you want to create a great instagram piece out all the best scenes across Netflix films of people shouting “Merry Christmas”!
TechCrunch
MARCH 22, 2022
Films weren’t always widescreen. Originally they were more likely to be approximately the shape of a 35mm film frame, for obvious reasons. If you matted out the top and bottom, you could project a widescreen image, which people liked — but you were basically just zooming in on a part of the film, which you paid for in detail.
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