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Foundation models have the potential to change the way organizations build artificial intelligence (AI) and train with machine learning (ML). To that end, IBM announced today that it has developed and contributed code to the open-source PyTorch machine learning project to enable the technology to work more efficiently with commodity ethernet-based networking. IBM has also built an open-source operator that helps to optimize the deployment of PyTorch on the Red Hat OpenShift platform, which is based on the open-source Kubernetes cloud container orchestration project. With the PyTorch Foundation, more open-source innovation is now possible Until September, PyTorch had been operated as an open-source project managed by Meta. There has also been limited support for developers wanting to build a foundation model with an entirely open-source stack. In addition to the code improvements in PyTorch, IBM has also worked to enable the open-source Red Hat OpenShift Kubernetes platform to support the development of foundation models. “I think it [PyTorch Foundation] will improve open-source collaboration,” Ganti said. A key challenge for building foundation models is that, to date, they have generally required the use of specific types of networking and infrastructure hardware to run efficiently. ( Continue reading.