The Knowm API is our special Machine Learning (ML) library. It is the result of over a decade of research and development. It can be used to solve problems across many domains of machine learning, from classification, prediction, and anomaly detection to feature-learning, robotic actuation, and combinatorial optimization. It is a collection of ML modules built on Thermodynamic Random Access Memory (kT-RAM), a general-purpose adaptive memristor processor designed on the principles of Anti-Hebbian and Hebbian (AHaH) Computing.
kT-RAM is a fundamentally new type of computing substrate that resolves a serious problem in machine learning, or any other computational program where lots of memory must be ‘adapted’ and ‘integrated’ constantly. Every modern computing system currently separates memory and processing. This works well for many tasks, but it fails for large-scale adaptive systems like brains or large ML models like neural networks. Indeed, there is no system in Nature outside of modern human digital computers that actually separates memory and processing, so it’s a wonder we have been able to do as much as we have. kT-RAM provides a universal adaptation or learning substrate and solves, in physically adaptive hardware, the learning problems that we would otherwise have to compute by shuttling information back and forth between memory and processing.
The Knowm API is a software hook to kT-RAM, where machine learning functions have been reduced to kT-RAM instruction set routines.