Twelve Labs: Multimodal AI That Understands Videos like Humans

In this interview from NAB 2024 in Las Vegas, Anthony Giuliani of Twelve Labs describes his company's sophisticated approach to analyzing video content. This approach enables a human-like interpretation without relying on traditional metadata, and allows users to search, classify, and execute other tasks with videos by understanding various elements such as sound, speech, actions, and even visual cues like logos.
The implications are profound across many industries, including entertainment, sports, and security. By extracting metadata dynamically, the system enhances content discoverability and management, streamlining workflows and significantly improving the accuracy and relevance of search results within large video datasets.
Contents:
00:00:00 - Introduction to Twelve Labs and their video metadata extraction technology.
00:00:49 - Explanation of multimodal video understanding models that interpret videos similarly to human cognition.
00:01:40 - Discussion on the role of video embeddings in eliminating the need for traditional metadata while complementing it where available.
00:02:29 - Insights into the various modalities processed by their technology, including audio, speech, and visual cues.
00:03:26 - Overview of current users and applications, highlighting the involvement of enterprise customers like the NFL.
00:06:14 - Challenges in developing technology that provides a human-like understanding of video content.
00:11:47 - Potential future enhancements and the flexibility of video embeddings compared to traditional tagging methods.