we have MONAI. It's open source under an Apache 2.0 license that allows it to be used for both academic and commercial purposes. It builds on top of PyTorch and it's really an amazing foundation both for research as well as product development. Not just for training AI systems, but also doing like AI assisted annotation and MONAI labeling, as well as deploying those AI systems in the field in clinical environments. How wide is the adoption of this tool today? We track multiple metrics to identify its adoption. One is the number of downloads and we're at 3.3 million downloads for MONAI, since the initial release in 2020. It's amazing! We also have an arXiv paper that we ask people to cite and it has over 600 citations associated with it. But what really warms my heart, the metric that I like, is when I walk around conferences such as MICCAI and I see MONAI being mentioned during presentations. Or a student comes up to me and says: “Hey, you're Stephen Aylward from MONAI. I love MONAI! It's been such a wonderful impact on my PhD dissertation!” Or “It's had a wonderful impact on my master's thesis!” What is the secret of MONAI? Why do you think people like it so much? I think the credit goes to Jorge Cardoso at King's College London and Prerna Dogra at NVIDIA because they began by involving the community, as they realized that it had to be community involvement from the start. 29 Computer Vision News Computer Vision News with Stephen Aylward - NVIDIA
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