MetaTF development environment to simplify deep learning
BrainChip, a provider of high-performance AI technology, has introduced MetaTF, a versatile ML framework that allows people working in the convolutional neural network space to quickly and easily move to neuromorphic computing.
The MetaTF development environment is an easy-to-use, complete machine learning framework for the creation, training and testing of neural networks, supporting the development of systems for Edge AI on BrainChip’s Akida event domain neural processor.
The MetaTF development environment leverages TensorFlow and Keras for industry-standard neural network development and training and includes the Akida Execution Engine (chip simulator), data-to-event converters, and a model zoo of pre-trained models. The framework leverages the Python scripting language and its associated tools and libraries, including Jupyter notebooks and NumPy.
Deep-learning professionals do not need to learn a new framework to start using MetaTF immediately. In three simple steps, MetaTF users can go from designing and training CNNs to converting them for deployment on the Akida neural processor to fully leverage neuromorphic computing and overcome the challenges of AI at the Edge. By minimising complexity and reducing wasted time in development, BrainChip is enabling organisations to maximize resources and minimise project times for greater ROI.
“AI doesn’t have to be complex and people don’t have to know how to program neuromorphic computing to take advantage of its benefits,” said Anil Mankar, Chief Development Officer at BrainChip. “The future is SNN and we’ve built an easy way to get there. With MetaTF, we introduce another piece of the puzzle that allow users to quickly and easily train, convert and deploy ML models to Akida while working in their current software environments.”