NOVEMBER 16, 2017

Announcing ONNX support for Apache MXNet

Today, AWS announces the availability of ONNX-MXNet, an open source Python package to import ONNX (Open Neural Network Exchange) deep learning models into Apache MXNet (Incubating). MXNet is a fully featured and scalable deep learning framework, that offers APIs across popular languages such as Python, Scala and R. With ONNX format support for MXNet, developers can build and train models with other frameworks, such as PyTorch, Microsoft Cognitive Toolkit (CNTK), or Caffe2, and import these models into MXNet to run them for inference using MXNet’s highly optimized and scalable engine. READ MORE

NOVEMBER 16, 2017

Amazon Web Services to join ONNX AI format, drive MXNET support

The Open Neural Network Exchange (ONNX) is a community project originally launched in September 2017 to increase interoperability between deep learning tools. ONNX is a standard for representing deep learning models that enables these models to be transferred between frameworks. It is the first step toward an open ecosystem where AI developers can easily move between state-of-the-art tools and choose the combination that works best for them. READ MORE

NOVEMBER 16, 2017

Support for open AI ecosystem grows as Amazon Web Services joins ONNX AI format

It’s been an exciting few months! In September we introduced the Open Neural Network Exchange (ONNX) format that we created with Facebook to increase interoperability and reduce friction for developing and deploying AI. In October a number of companies that share our goals announced their support for ONNX. READ MORE

OCTOBER 11, 2017

Open standards for deep learning to simplify development of neural networks

Among the various fields of exploration in artificial intelligence, deep learning is an exciting and increasingly important area of research that holds great potential for helping computers understand and extract meaning from data, e.g. deciphering images and sounds.

To help further the creation and adoption of interoperable deep learning models, IBM joined the Open Neural Network Exchange (ONNX), a new industry ecosystem that was established by Facebook and Microsoft in September. ONNX provides a common open format to represent deep learning models. The ONNX initiative envisions the flexibility to move deep learning models seamlessly between open-source frameworks to accelerate development for data scientists. READ MORE

OCTOBER 10, 2017

ONNX AI Format Adds Partners

Today, following the introduction of the Open Neural Network Exchange (ONNX) format on September 7, AMD, ARM, Huawei, IBM, Intel, Qualcomm have announced their support for ONNX. These companies, like Facebook and Microsoft, recognize the benefits ONNX’s open ecosystem provides engineers and researchers by allowing them to more easily move between state-of-the-art machine learning tools and choose the best combination for their projects. ONNX also makes it easier for optimizations to reach more developers. Any tools exporting ONNX models can benefit ONNX-compatible runtimes and libraries designed to maximize performance on some of the best AI hardware in the industry. READ MORE

OCTOBER 10, 2017

Microsoft and Facebook Call for Open AI Ecosystem Gaining Broader Industry Momentum.

Last month we introduced the Open Neural Network Exchange (ONNX) format with Facebook to increase interoperability and reduce friction for developing and deploying AI. Since then we’ve talked with many companies that share our goals and recognize the benefits of the ONNX open ecosystem. READ MORE

OCTOBER 10, 2017

AMD announces ONNX support

AMD is excited to see the emergence of the Open Neural Network Exchange (ONNX) format bring common format model to bridge three industry-leading deep learning frameworks ( Pytorch, Caffe2, and CNTK) to give our customer simpler path to explore their networks via rich foundation of framework interoperability. READ MORE

OCTOBER 10, 2017

Arm joins Facebook and Microsoft to bring next-generation AI to life

At Arm, our commitment to artificial intelligence (AI) starts with developing and delivering technologies that are secure, scalable, and power-efficient. After all, AI is already simplifying and transforming our lives, but we’re really only scratching the surface of what’s possible. AI will increasingly happen on end device systems whether it’s your smartphone or your car, which means we’ll continue to see more compute power and AI algorithms. As part of that effort, we’re excited to announce that we’ve joined industry leaders on an open-source project that aims to enable interoperability and innovation in the AI framework ecosystem. READ MORE

OCTOBER 10, 2017

QTI announces support for ONNX, simplifying AI choices for developers

QUALCOMM - So you’ve started working with neural networks and artificial intelligence (AI), but did you find it hard to choose one machine learning framework over another – like Caffe/Caffe2, TensorFlow Cognitive Toolkit or PyTorch? Whether you’re training your own models or using freely available ones, you’ll want to choose a framework that you stick with all the way through production. READ MORE

OCTOBER 10, 2017

Intel Joins Open Neural Network Exchange Ecosystem to Expand Developer Choice in Deep Learning Frameworks

As part of Intel’s commitment to furthering artificial intelligence across the industry, Intel is joining Microsoft*, Facebook*, and others to participate in the Open Neural Network Exchange (ONNX) project. By joining the project, we plan to further expand the choices developers have on top of frameworks powered by the Intel® Nervana™ Graph library and deployment through our Deep Learning Deployment Toolkit. Developers should have the freedom to choose the best software and hardware to build their artificial intelligence model and not be locked into one solution based on a framework. Deep learning is better when developers can move models from framework to framework and use the best hardware platform for the job. READ MORE

SEPTEMBER 7, 2017

Facebook and Microsoft introduce new open ecosystem for interchangeable AI frameworks

Facebook and Microsoft are today introducing Open Neural Network Exchange (ONNX) format, a standard for representing deep learning models that enables models to be transferred between frameworks. ONNX is the first step toward an open ecosystem where AI developers can easily move between state-of-the-art tools and choose the combination that is best for them. READ MORE

SEPTEMBER 7, 2017

Microsoft and Facebook create open ecosystem for AI model interoperability

At Microsoft our commitment is to make AI more accessible and valuable for everyone. We offer a variety of platforms and tools to facilitate this, including our Cognitive Toolkit, an open source framework for building deep neural networks. We also work with other organizations that share our views to help the AI community.

Today we are excited to announce the Open Neural Network Exchange (ONNX) format in conjunction with Facebook. ONNX provides a shared model representation for interoperability and innovation in the AI framework ecosystem. Cognitive Toolkit, Caffe2, and PyTorch will all be supporting ONNX. Microsoft and Facebook co-developed ONNX as an open source project, and we hope the community will help us evolve it. READ MORE