Deep Learning is now powering numerous AI technologies in daily life, and convolutional neural networks (CNNs) can apply complex treatments to images at high speeds. At Unity, we aim to propose seamless integration of CNN inference in the 3D rendering pipeline. Unity Labs, therefore, works on improving state-of-the-art research and developing an efficient neural inference engine called Barracuda. Deep learning has long been confined to supercomputers and offline computation, but their usability at real-time on consumer hardware is fast approaching thanks to ever-increasing compute capability. With Barracuda, Unity Labs hopes to accelerate its arrival in creators' hands.

One of Unity Labs' missions is identifying and supporting cutting edge research. For 2017, we have identified a slate of research topics we are currently working on in the areas not limited to VR and AR authoring tools, Game AI, and Graphics. It's our vision to advance the next generation of 3D interactive entertainment content authoring. Over the past weeks, we've joined forces with Unity's AI & Machine Learning Group to identify and support graduate researchers specifically working on research challenges in Machine Learning for games. The current perception of Machine Learning in the games industry is surrounding the potential that learning has to offer the gaming world.