Created as a partnership between Facebook and Microsoft, Open Neural Network Exchange formats, or ONNX for short, is an open format that will assist engineers in sharing artificial intelligence (AI) models across various frameworks. Support for ONNX was brought about by Facebook through changes to PyTorch and Caffe2 in an effort to combine operators between these different frameworks.
Simply put, ONNX will serve as a sort of open access bridge for future AI projects that developers wish to be compatible with this new and exciting format. ONNX will allow models to be exchanged freely and to be compatible throughout multiple different frameworks.
What Need Does ONNX Satisfy?
Before the introduction of this format, engineers would oftentimes find themselves forced to choose a particular AI framework. While there are many great frameworks available, having to stick with one in particular was extremely limiting for those working on further advancements in artificial intelligence. With the introduction of ONNX, those working on AI research and development are now able to utilize multiple different models across many frameworks, as long as they are made to be compatible with ONNX. In a way, this program is helping to drive the transition of artificial intelligence development away from proprietary frameworks towards a more open-source method for sharing AI models.
Which Notable Industry Partners are Involved with This Project?
As previously mentioned, Facebook and Microsoft are the two leading corporate partners for the ONNX project. In addition to these two industry leaders, multiple other industry players, such as Amazon Web Services, AMD, and Nvidia have expressed interest in contributing to the project into the future.
One of the most exciting facets of the Open Neural Network Exchange project is just how much interest this topic is generating throughout the artificial intelligence sector. With so much hype and interest surrounding the project, it is almost certain that it will continue to become more and more popular as aspiring artificial intelligence engineers and enthusiasts familiarize themselves with the project and its implications.
How Can One Take Advantage of the ONNX Platform?
For starters, those wanting to take advantage of the ONNX platform can further familiarize themselves with the new format here. There are also some very useful tutorials on GitHub, which can help developers and engineers the headache of trying to figure out this new format on their own or with their colleagues.
After becoming more familiar with the Open Neural Network Exchange format project, those who want to leverage this new technology while working on developing new models would be wise to retroactively edit their previous projects in a way that makes them ONNX-compatible. While this may be a tedious task, it will help to ensure that future projects will be able to take full advantage of the groundbreaking possibilities that ONNX will provide in the future.
Open Neural Network Exchange Formats: The Future of Cross-Platform AI!
As the international community of artificial intelligence enthusiasts continues to push for widespread adoption of the technology, cross-framework formats such as ONNX provide an exciting next step towards the realization of this dream. As the Open Neural Network Exchange format continues to gain notoriety within the industry, it will likely allow for more robust artificial intelligence features to be factored into all sorts of products, which is truly an exciting future for even casual artificial intelligence enthusiasts.