IBM Analog AI: Revolutionizing The Future Of Technology
Process of encoding information as a physical quantity and doing calculations utilizing the physical characteristics of memory devices
Non-volatile memory devices, which can retain data for up to ten years without power, are used in analog AI
Synaptic weights are locally stored in the conductance values of nanoscale resistive memory devices in analog AI
The von Neumann bottleneck, which restricts calculation speed and efficiency, is removed by analog AI, which stores and processes data in the same location
Analog AI performs matrix multiplications in an analog fashion by utilizing the physical characteristics of memory devices
Training and inference are two distinct deep learning tasks that may be accomplished using analog in-memory computing
For example, you would supply a collection of labeled photographs for the training exercise if you want your model to recognize various images