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NVIDIA Run:ai accelerates AI and machine learning operations by addressing key infrastructure challenges through dynamic resource allocation, comprehensive AI life-cycle support, and strategic resource management. By pooling resources across environments and utilizing advanced orchestration, NVIDIA Run:ai significantly enhances GPU efficiency and workload capacity. With support for public clouds, private clouds, hybrid environments, or on-premises data centers, NVIDIA Run:ai provides unparalleled flexibility and adaptability.
Neptune.ai is an experiment tracking hub bringing organization and collaboration to data science projects. Neptune records your entire experimentation process - exploratory notebooks, model training runs, code, hyperparameters, metrics, data versions, results, exploration visualizations, and more. Everything is stored and backed-up in an organized knowledge repository, ready to be accessed, analyzed, shared, and discussed with your team. No matter what type of problems you are working on, Neptune fits them all, from evaluating credit risk to finding the nuclei in divergent images.
Snorkel AI started as a research project in the Stanford AI Lab in 2016, where they set out to explore a higher-level interface to machine learning through programmatically labeled and managed training data. From deploying early versions of Snorkel Flow's core technology with some of the world’s leading organizations, to empowering scientists, doctors, and journalists, they’ve seen firsthand how this approach democratizes and accelerates AI. Now, they’re working to bring their technology to everyone.
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