Topic: Memory requirements

Join Yasuo Tabei’s Succinct Information Processing Team to research efficient AI systems. Topics include memory and knowledge management for language models and agents; reusable skills from agent execution histories; algorithms that reduce computing and memory requirements; and AI operating under device, edge and communication constraints. The researcher will formulate problems, implement methods, evaluate reliability and efficiency, publish papers and release software. The Tokyo position uses renewable annual contracts, with maximum terms of seven years for research scientists and five for po

Deep learning has made tremendous progress in the last year but it's high computational and memory requirements impose challenges in using deep learning on edge devices. There has been some progress in lowering memory requirements of deep neural networks (for instance, use of half-precision) but there has been minimal effort in developing alternative efficient computational paradigms. Inspired by the brain, Spiking Neural Networks (SNN) provide an energy-efficient alternative to conventional rate-based neural networks. However, SNN architectures that employ the traditional feedforward and feed