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Samsung backs a video AI startup that can analyze thousands of hours of footage

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Many AI tools can look at a video today and summarize what is going on, but things become a bit tricky when you ask models questions about multiple videos and footage spanning many hours.

This is a big limitation for security companies that want to use AI to scrub through thousands of hours of footage from different cameras, as well as marketing companies that want to study different video campaigns and product shoots.

Memories.ai wants to tackle that problem with its AI platform that can process up to 10 million hours of video. For companies with a lot of video to analyze, the startup wants to provide a contextual layer, complete with searchable indexing, tagging, segments and aggregation.

Its co-founder Dr. Shawn Shen was a research scientist at Meta’s Reality Labs while he was pursuing his PhD, and his counterpart Enmin (Ben) Zhou worked at Meta as a machine learning engineer.

“All top AI companies, such as Google, OpenAI and Meta, are focused on producing end-to-end models. Those capabilities are good, but these models often have limitations around understanding video context beyond one or two hours,” Shen told TechCrunch.

“But when humans use visual memory, we sift through a large context of data. We were inspired by this and wanted to build a solution to understand video across many hours better,” he said.

Image Credits: Memories.ai

Towards that goal, the company has now raised $8 million in a seed funding round led by Susa Ventures, and with participation from Samsung Next, Fusion Fund, Crane Ventures, Seedcamp, and Creator Ventures. Shen said the company initially aimed to raise $4 million, but ended up with an oversubscribed round because of investor interest.

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“Shen is a highly technical founder, and he is obsessed with pushing boundaries of video understanding and intelligence,” said Misha Gordon-Rowe, a partner at Susa Ventures. “Memories.ai can unlock a lot of first-party visual intelligence data with its solution. We felt that there was a gap in the market for long context visual intelligence, which attracted us to invest in the company,” he added.

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