Growing computational demands from deep neural networks (DNNs), coupled with diminishing returns from general-purpose architectures, have led to a proliferation of Neural Processing Units (NPUs). In this talk, we will discuss Project Brainwave, a production-scale system for real-time (low latency and high throughput) DNN inference. Brainwave NPU is reconfigurable and deployed in scale production. This reconfigurability, in turn, eliminates costly silicon updates to accommodate evolving state-of-the-art models while enabling orders of magnitude performance improvement compared to highly optimized software solutions.