Is Artificial Intelligence Already Streamlining Its Own Supply Chain?

We're now in a phase of computing increasingly characterized by engineering complex systems of automation by applying several new and convergent technologies including: deep learning, cloud computing and massive arrays of data-producing sensors. NVIDIA's deep learning GPUs have been at the center of partnerships or agreements with a multitude of companies and customers. For example, NVIDIA partnered with U.S.-based Tesla Motors to provide deep learning GPUs for autonomous driving, Japan-based FANUC Robotics to create a deep learning "factory manager" to oversee manufacturing robots that manufacture other manufacturing robots, U.S.-based Amazon Web Services to provide a web platform to create deep learning applications, China-based Hikvision to power the company's sophisticated systems of video surveillance, and Japan-based Komatsu's SMARTCONSTRUCTION mining and construction equipment vehicles. If you stop to take account of how many deep learning partnerships NVIDIA has entered into with powerful commercial entities in various sectors of global industry, it quickly becomes overwhelming. But how does NVIDIA and its manufacturing partners apply deep learning along the supply chain that produces NVIDIA GPUs?