Apple buys computer vision & artificial intelligence startup Vilynx for $50 million

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Earlier in 2020, Apple reportedly purchased Barcelona startup Vilynx, gaining expertise and technologies related to artificial intelligence, machine learning, and computer vision.

Citing sources familiar with the matter, a report on Tuesday claims that the Barcelona, Spain based startup was purchased to enhance Apple's artificial intelligence work as a whole. A mission statement about the company says that the company can "add rich metadata to enable search and social sharing."

The company also claims that the metadata makes convent instantly discoverable. Tailored information is provided to creators by the company's software to determine "which portions of the video have the most views and which are not getting attention."

The CrunchBase profile of the company was recently updated to reflect that the company is now in Palo Alto, California.

Co-founder Juan Carlos Riviero was interviewed in 2018, discussing the company and what it does.

"To be truly valuable to media companies, AI must offer an understanding of their content— not just reams of crunched data or recognition of faces and buildings. That's exactly what the self-learning Vilynx brain does," said Riviero. "Yes, it analyzes faces, processes speech, reads text and identifies buildings and places— but then it takes the crucial step of putting all this into context."

In a report on Tuesday, Bloomberg stated that Apple is intending to apply the technology to Siri and search. Apple's Photos could be improved with the technology to search stored video, and also, possibly for News and Apple TV apps for a recommendation engine.

The purchase is just the latest in a long chain of AI-related acquisitions that started with Perceptioin 2015. Apple went on to buy out Turi and Tuplejump in 2016, and Laserlike in 2019.

In January 2020, Apple purchased, a specialist in low-power edge-based artificial intelligence. Later in the year, Apple purchased Inductiv, bringing AI to automatically identify and correct errors in large data sets.