I’m reading this article and it talks about the classic von Neumann architecture, then goes onto say this: “The DigAn technology has enabled Ambient Scientific to create a configurable matrix computer at chip level. This fundamentally new approach includes a new type of compute unit, the analog MAC. This block does the work of the von Neumann architecture’s ALU and memory units (see Figure 3). The analog MAC is optimized for AI systems, in which MAC operations represent 95% of the compute workload. It enables in-memory computing, thus solving the von Neumann architecture’s problem of physical separation between the memory and compute blocks. This is thanks to another Ambient Scientific innovation, the HyperPort 3D memory architecture, which enables vertical stacking of memory elements at each MAC unit. The second weakness of the von Neumann architecture in neural network operations is the vastly inefficient way in which it compiles a neural networking model into instructions. We solve this by creating a matrix computer. It arranges analog MAC blocks to mirror the topology of a neural network. Each DigAn unit is a single monolithic circuit that computes an entire layer of neurons in a single cycle. As shown in Figure 4, multiple layers of DigAn circuits can be scaled up into a matrix computer that mirrors the structure of a neural network.” Could someone who understands this tech a lot better than me tell me what this is actually saying? How does this change AI? What are the potential applications? What makes this different? submitted by /u/DisastrousFlyover
Originally posted by u/DisastrousFlyover on r/ArtificialInteligence