DOI: https://doi.org/10.29363/nanoge.neuronics.2024.004
Publication date: 18th December 2023
This talk presents the NimbleAI approach, which leverages the key principles of energy-efficient light sensing in eyes and visual information processing in brains. Inspired by these principles, NimbleAI is creating an integral sensing-processing neuromorphic chip that builds upon the latest advances in 3D stacked silicon integration. In NimbleAI, a frugal always-on sensing stage builds basic understanding of the visual scene and drives a multi-tiered collection of highly specialised event-based pre- and post-processing kernels and neural networks to perform visual stimuli inference using the bare minimum amount of energy. Since manufacturing a full 3D testchip is prohibitively expensive, NimbleAI prototypes key components via small-scale 2D stand-alone testchips. This cost-effective use of silicon allows us to readjust direction during project execution to produce silicon-proven IP and high confidence research conclusions. To enable the global research community to use our results, we will deliver a prototype of the 3D integrated sensing-processing NimbleAI architecture with the corresponding programming tools. The prototype will be flexible to accommodate user IP and will combine commercial neuromorphic chips and NimbleAI testchips.
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