Technical, financial, and societal factors have driven innovation activity in the AI hardware space to an all-time high. Such drivers include new applications with low latency demands, a massive increase in compute requirements to train and run modern AI models, limited network bandwidth, and privacy and cybersecurity requirements. Indeed, companies both big and small are responding to these drivers by building processor and memory technologies that are specifically tailored to handle AI workloads. Building off of our previous report on edge computing, we provide a taxonomy for the emerging AI hardware technology landscape and provide an estimated timeline of when clients can expect these technologies to begin gaining traction.
