The platform which attracts about 44% of all internet users and second most visited site in the world — The YouTube.
Some interesting facts about YouTube:
- More than 70% of what people watch on YouTube is determined by its recommendation algorithm.
- 1 billion hours of YouTube content is watched per day.
- 37% of all mobile internet traffic belongs to YouTube.
- YouTube is technically the second largest search engine in the world.
- There are 31 million+ YouTube channels out there.
- The videos are not ranked on their view count but they are ranked on their watch time.
- 62% of businesses use YouTube.
What is Artificial Intelligence?
Artificial Intelligence(AI) refers to the simulation of human intelligence in machines that are programmed to think like humans. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
What is Machine Learning?
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
- In 2016, YouTube released a whitepaper that made some waves. In it, product engineers described the role of deep neural networks and machine learning in the platform’s recommendation system.
How YouTube is benefited from AI/ML?
New effects on videos:
- Google’s artificial intelligence researchers trained a neural network to be able to swap out backgrounds on video without the need for specialized equipment.
- While it’s been possible to do this for decades — think green screens that are replaced by digital effects — it was a complicated and time-consuming process.
- The researchers trained an algorithm with carefully labeled imagery that allowed the algorithm to learn patterns
Up Next feature:
- If you have used YouTube’s “Up Next” function then you are benefited from their artificial intelligence.
- Dataset on YouTube is constantly changing day by day as its user upload hours of videos every single minutes.
- So, AI requires to power its recommendation engine and it should be very effective and different than recommendation engine of Netflix or Spotify.
- while new data is added, it has to be able to handle real-time recommendations.
- So, they come with two solutions: 1) candidate generation, where the algorithm assesses the YouTube history of the user. 2) the ranking system that assigns a score to each video.
Removal of objectionable content:
- Number of videos removed from YouTube worldwide from 4th quarter 2017 to 2nd quarter 2020:
- ML involves training algorithms on data so that they become able to spot patterns and take actions by themselves, without human intervention. In this case, YouTube uses the technology to automatically spot objectionable content.
- In the first quarter of this year, 8.3 million videos were removed from YouTube, and 76% were automatically identified and flagged by AI classifiers.
- More than 70% of these were identified before there were any views by users.
- Before using artificial intelligence, only 8% of videos containing “violent extremism” (banned on the platform) were flagged and removed before ten views had occurred.
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Thanks for reading!! :)
