"The dataset was created from over 7 million YouTube videos (450,000 hours of video) and includes video labels from a vocabulary of 4716 classes (3.4 labels/video on average," Google wrote on the competition page. "It also comes with pre-extracted audio & visual features from every second of video (3.2B feature vectors in total)."

Google says it'll announce the winning teams at the YouTube-8M Workshop held during the IEEE Conference on Computer Vision and Pattern Recognition in July. With up to $30,000 awarded per team, there's a good chance Google will end up attracting some eager developers. The company is also offering some free Google Cloud credits to early participants.

While the results of the competition won't directly affect consumers for a while, Google software engineer Paul Natsev notes that whatever they learn will be useful across many different types of videos. Hopefully, that could lead to better searching and content filtering down the line on YouTube.