The ability to share AI and ML datasets, processing engines and the other working paraphernalia of Deep Learning (DL) through open (and indeed open source) platforms, channels and communities is argued to be a more productive way for the machines themselves to learn more naturally.
This June 2020 also saw Abbyy launch its NeoML open source library for building, training and deploying Machine Learning models.
Where Databricks’ open intelligence technology works on big data processing and cloud computing ‘cluster’ management.
In Abbyy’s case the Machine Learning framework is optimized for image processing tasks and offers fast performance for pre-trained models running on any device.
The company says that as open source becomes a staple in the development of mission-critical software, with 95% of IT leaders asserting that it is strategically important.
In the case of Abbyy’s NeoML, the technology supports the Open Neural Network Exchange (ONNX), a global open ecosystem for interoperable ML models, which is hoped to improve compatibility of tools making it easier for software developers to use the right combinations to achieve their goals.