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AI on public cloud with open source

Learn why you should use open source tooling for your AI projects on the public cloud

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About the webinar

AI is at the heart of a revolution in the technology space. From oil & gas to public sector, from telco to retail, all departments from all industries are looking for ways to put AI to work. Once organisations have finalised use case assessment, their next question is typically related to the environment they will use to develop and deploy their AI initiatives.

They often prefer the public clouds as an initial environment, because of the computing power and ability to scale as projects mature. In addition to the infrastructure, enterprises need software where they can develop and deploy the machine learning models. Open source tools such as Jupyter Notebooks or MLflow are a great starting point and enable you to have a consistent experience on any cloud for your ML workloads. When scaling projects, the need for MLOps platforms such as Charmed Kubeflow is absolutely obvious.

Join our webinar on April, 2 to learn more about open source tooling for AI on public cloud. Led by Aaron Whitehouse, Senior Public Cloud Enablement Director, and Andreea Munteanu, AI Product Manager, the webinar will cover:

  • Scenarios in which open source tooling on public cloud solves a problem for AI initiatives
  • Main benefits of using open source tooling on the public cloud for AI projects
  • Use cases from our customers
  • Hybrid cloud and multi cloud opportunities for AI projects