Snapchat used AI agents to build a sound-aware model that captions your videos

They used "teachers" to describe 3.8M videos for their Panda-70M dataset

Understanding video content poses a monumental challenge for artificial intelligence (AI). Unlike static images, videos contain complex spatial, temporal, and audio signals that must be interpreted across multiple modalities. To make progress, AI systems need massive datasets for training - far larger than what's available today.

Now, researchers from Snap, UC Merced, and the University of Trento have taken a major step forward with Panda-70M (paper, project site). This pioneering dataset provides 70 million high-resolution YouTube video clips paired with descriptive captions.

In this in-depth look, we'll cover:

• Why video-text data is critical yet lacking in the AI space

• How Panda-70M's automated pipeline works

• What results show about Panda-70M's value

• Limitations and future directions for ever-larger datasets

Let's dive in!

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