Bismit
Biologically Inspired Sensory Motor Inference Toolkit
Bismit is one of the first members of the next paradigm of cortical learning libraries. Going beyond simple Bayesian neural networks and incorporating ideas from the theory of hierarchical temporal memory, such as sparse distributed representations and temporal context, Bismit is a brain building framework for designing truly intelligent machines. It is not a typical machine learning or deep learning platform and does not function like a traditional neural network.
Goals
To create:
- A toolkit that is simple enough to be useful now and be flexible enough to absorb future neuroscientific discoveries. We know enough now about the basic architecture of the brain that we can create a scaffold with enough wiggle room to be refined as more is learned.
Structure
Bismit simulates the interactions of the following hierarchical structures of the neocortex:
Cortex - Region - Area - Layer - Slice - Cell - Tuft - Dendrite - Synapse
Bismit is written in Rust and OpenCL C and is in an unstable pre-alpha stage. Full basic sensory functionality is complete. Motor control and use case development are underway. See the vibi project (currently in early development) for an OpenGL based visualization frontend.