Source Code for “Self Driving Car Learns Online and On-board on Raspberry Pi 3”

Hello! In the previous post, we demonstrated a self-driving model car that performed all processing on-board on a Raspberry Pi 3. We have now released the code for the car and associated tools. The following repositories are available on GitHub: EOgmaNeo – the primary library containing our super-fast online learning technology! EOgmaDrive – a description…

Exponential Memory

Hello! We have been working hard on the latest version of OgmaNeo, and in the latest version (v1.3) introduced something we call “Exponential Memory”. We believe this to be an important step forward that applies not only to what we have in OgmaNeo already, but also to Deep Learning in general. In simplest terms, Exponential…

OgmaNeo Ball Physics Simulation

The following is a rundown of a new demo added to the OgmaNeoDemos repository, Ball Physics Prediction. We plan to release new demos regularly! Ball Physics Prediction/Simulation An important aspect of world modeling in humans is the ability to simulate physical interactions ahead of time. Let’s try to make a simple demo of this using OgmaNeo!…

OgmaNeo Overview and Video Prediction

Here is an overview of the Feynman Machine architecture used in the OgmaNeo library, followed by an example for video prediction (recall). For the original Feynman Machine paper, see https://arxiv.org/abs/1609.03971. A High Level Look at the Feynman Machine The Feynman Machine is a hierarchical sequence prediction algorithm that functions on the basis of coupled dynamical systems.…

Introducing OgmaNeo – Machine Learning based on Neuroscience

November 2016 – Ogma is pleased to announce the release of its OGMANEO software library, alongside usage examples and demonstrations, and language bindings for Java™ and Python™. The OgmaNeo library contains implementations of Online Predictive Hierarchies, as described in the paper: “Feynman Machine: The Universal Dynamical Systems Computer” (http://arxiv.org/abs/1609.03971). In September, our paper was listed as among…