Non-von Neumann computing using neuromorphic systems based on 2-terminal resistive non-volatile memory elements has emerged as a promising approach, but its full potential has not been realized due to the lack of materials and devices with the appropriate attributes. Unlike memristors, which require large write currents to drive phase transformations or filament growth, electrochemical random access memory (ECRAM) decouples the ‘write’ and ‘read’ operations using a ‘gate’ electrode to tune the conductance state through charge transfer reactions, and every electron transferred through the external circuit in ECRAM corresponds to the migration of ∼1 ion used to store analogue information. Like static dopants in traditional semiconductors, electrochemically inserted ions modulate the conductivity by locally perturbing a host’s electronic structure; however, ECRAM does so in a dynamic and reversible manner. The resulting change in conductance can span orders of magnitude, from gradual increments needed for analog elements, to large, abrupt changes for dynamically reconfigurable adaptive architectures. In my presentation, I will briefly cover the history of ECRAM, the recent progress in devices spanning organic, inorganic, and 2D materials, circuits, architectures, and discuss the rich portfolio of challenging, fundamental questions and how we can harness ECRAM to realize a new paradigm for low power neuromorphic computing.