  Computing is bottlenecked by data. Large amounts of application data
overwhelm storage capability, communication capability, and computation
capability of the modern machines we design today. We argue that an intelligent
architecture should be designed to handle data well. We show that handling data
well requires designing architectures based on three key principles: 1)
data-centric, 2) data-driven, 3) dataaware. We give several examples for how to
exploit each of these principles to design a much more efficient and high
performance computing system. We discuss how to enable adoption of such
fundamentally more intelligent architectures, which we believe are key to
efficiency, performance, and sustainability. We conclude with some guiding
principles for future computing architecture and system designs. This
accompanying short paper provides a summary of the associated invited talk at
DATE 2021 and points the reader to further work that may be beneficial to
examine.
