tinyML On Device Learning Forum – Guy Paillet: NeuroMem® wearable, hardwired sub milliwatt real time

NeuroMem® wearable, hardwired sub milliwatt real time machine learning with wholy parallel access to “neuron memories” fully explainable
Guy PAILLET, Co-founder, General Vision

NeuroMem is a fully hardwired, instant, incremental “learn and recognize” ML technology featuring response such as identified (one or many categories), uncertain and unknown (e.g. anomalies detection among others) with incremental learning without software of the unknown. NeuroMem fulfill the request of DARPA for explainable AI (capability of
“behavior justification”). The ZISC was born at Paris in IBM Labs in 1993 co-patented by IBM Corp. and Guy Paillet as ZISC (https://en.wikipedia.org/wiki/No_instruction_set_computing )
The TinyML technology had followed the semiconductor geometry evolution from 1 micron 36 neurons (ZISC36) to the incoming ANM5500 neurons (55 nm by TSMC) and more to come. Thousands of NeuroMem chips are in operation at customers site around the World mostly since 2010 but some since 2000 (some at sea on fishing vessel trained by sailors)
It is possible to put the real time learning and recognition inside of miniature devices such as a MEMS microphone, ball bearing or an image sensor (patented MIPD – Monolithic Image Perception Device). Accurate learning and recognition can be achieved at either 25 MHZ but can be also efficient at few dozens of hertz. Neurostamp, featuring a small low power FPGA and 4032 is a perfect example of the smallest device capable of making
anomalies detection which can be generalized in factories, automotive or more. Typically depending on operation power consumption, for exemple on NM500 (on the NeuroStamp can be from 50 microwatt to 3 milliwatts as there is no sofwareuning operation can be fully asynchronous.

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