Google needs your help building better video analysis algorithms

You probably haven't heard of YouTube-8M, but it's a big deal for anyone working in the field of machine learning. In short, it's a large database of labeled video content that programmers can use to test out their algorithms. Today, Google announced that YouTube-8M is getting a major update, with even more labels across more its videos, as well as audio elements. And the company is also aiming to make the dataset even better with a Kaggle competition, which will offer big bucks from a $100,000 prize pool to teams who build the best algorithms for tagging around 700,000 new videos (using the 8M dataset for training). "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.