Constructing deep learning systems today is thus still a largely bespoke process, involving crafting a customized solution tailored for the unique needs of each specific application.

First, we thought of traffic in terms of the physical process of diffusion. In our model, the flow of traffic over a network of roads is analogous to the flow of fluids over a surface — motions that ...

High-resolution flow field data are essential for accurately evaluating the aerodynamic performance of aircraft. However, acquiring such data via ...

By contrast, using a GPU-based deep-learning model would require the equipment to be bulkier and more power hungry. Another client wants to use Neural Magic to process security camera footage.