What Happened
In September 2017, ONNX (Open Neural Network Exchange) was announced as a standard format to represent and exchange models, aiming to reduce friction between training and deployment frameworks.
Why It Matters
Interoperability became increasingly important as teams mixed research frameworks with optimized production runtimes and specialized hardware. ONNX helped standardize model export/import workflows across an expanding ecosystem.
Technical Details
ONNX defines a computation-graph model and operator sets to represent neural networks for inference-centric workflows, enabling toolchains (converters, compilers, accelerators) to target a common representation.