Industrial Electronics

New Machine Learning Environment for SNNs Released

30 July 2018

Source: BrainChip HoldingsSource: BrainChip Holdings

BrainChip Holdings Ltd. has announced the release of the Akida Development Environment. The Akida Development Environment is a machine learning framework for the creation, training and testing of spiking neural networks (SNNs). It was also created to support the development of systems for edge and enterprise products on the Akida Neuromorphic System-on-Chip (NSoC).

Applications that benefit from the Akida solution include public safety, transportation, agricultural productivity, financial security, cybersecurity and health care.

The Akida Development Environment includes the Akida Execution Engine, data-to-spike converters and a model zoo of spiking neural network (SNN) models. The framework leverages the Python scripting language and its associated tools and libraries.

The Akida Execution Engine contains a software simulation of the Akida neuron, synapses and the multiple supported training methodologies. It can be accessed through API calls in a Python script. Users can specify their neural network topologies, training method and datasets for execution with the new environment. The execution engine supports multiple training methods, including unsupervised training and unsupervised training with a labeled final layer.

The development environment accepts spiking data created by Dynamic Vision Sensors (DVS). There are many other types of data that can be used with SNNs. Embedded in the Akida Execution Engine are data-to-spike converters, which convert common data formats such as image information (pixels) into the spikes required for an SNN. Users can create their own proprietary data to spike converters to be used within the development environment.

The Akida Development Environment is currently available on an early-access program to approved customers.

To learn more about the new development environment, visit BrainChip.

To contact the author of this article, email engineering360editors@globalspec.com


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