AI, Native Supercomputing and The Revival of Moore's Law

Based on Alan Turing's proposition on AI and computing machinery, which shaped Computing as we know it today, I argue that the new AI machine should understand linear algebra natively. In such a machine, a computing unit does not need to keep the legacy of a universal computing core. The data can be delivered to the computing units, and the results can be collected from them through Collective Streaming, reminiscent of Collective Communication in Supercomputing. There is no need for a deep memory hierarchy as in a GPU, nor a fine-grain mesh as in a systolic array.