Brackeys explores Photogrammetry to create a video game using 3D Scans of real world environments.
Samuel Arzt shows off a project where an AI learns to park a car in a parking lot in a 3D physics simulation.
The simulation was implemented using Unity’s ML-Agents framework (https://unity3d.com/machine-learning).
From the video description:
The AI consists of a deep Neural Network with 3 hidden layers of 128 neurons each. It is trained with the Proximal Policy Optimization (PPO) algorithm, which is a Reinforcement Learning approach.