Modern analog computing for solving differential and matrix equations

The paper discusses the resurgence of modern analog computing, emphasizing its capabilities in solving differential and matrix equations, and performing matrix-vector multiplications. It identifies resistive memory arrays as a particularly efficient hardware implementation, and surveys advancements in analog CMOS circuits that enhance these computational tasks. This work is significant for AI practitioners as it highlights the potential of analog computing to address the computational demands of data-intensive applications while exploring precision, scalability, and the relationship with in-memory computing.