A batch is essentially the smallest unit of work a curator can be paid for. It consists of a group of 15 frames of video presented one by one to curators for processing.

Why are batches important?

Traditionally, due to the optical flow of video, training AI models for video has been a time consuming and expensive process. Batches enable curators to quickly move through and accurately assess large amounts of visual data with ease.  For curators this means you can complete tasks quicker; increasing your hourly rate. For revealitTV it means we can train objects in video accurately and on demand.

Where do batches go once committed?

Once you have committed a batch at first it gets sent off for approval. Using a three phased approval algorithm revealitTV ensures that data curators are inputting is accurate and valid. Secondly, that data gets given to our Velocity product engine for training. This data trains our AI model to efficiently and effectively find objects in any frame of video.