Computer vision is a subset of machine learning that is used to allow computers to derive information from images, videos, and other outputs. This technology uses bounding boxes to bound different images or information in boxes, helping the machine understand what it is looking at. Data sets can be real-world or synthetic, and Unity provides tools to generate synthetic data or virtual environments to train a machine learning model.

The virtual environment can identify and bound different items in the scene, and there are various types of segmentation available, such as instant segmentation and 3D bounding boxes.

One of the most exciting developments in the field of machine learning is the ability to create fake data sets for training machine learning models using synthetic humans. With this technology, it is possible to generate completely fake people for facial recognition applications. The synthetic data set, called SynthFace, can train a machine learning model on a predictive outcome of facial recognition based on fake information.

This is a significant development in the field of machine learning as it reduces dwell time and accelerates model training. Additionally, the ability to create fake data sets in three dimensions opens up many possibilities in machine learning applications.