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AI models run on large amounts of good quality data, and when it comes to sensitive tasks like medical diagnosis or financial risk assessments, you need access to private data during both training and inference. When performing machine learning tasks in the cloud, enterprises are understandably concerned about data privacy as well as their model’s intellectual property. Additionally, stringent industry regulations often prohibit the sharing of such data.

It's the grand reveal of Ubuntu 24.04 Noble Numbat 👑 The numbat, a small enigmatic marsupial from Australia may not be the first creature that comes to mind when one ponders nobility. However, looks can be deceiving.

Curious how to start with Charmed MongoDB?

🚀 AI is reshaping our world, from entertainment to space exploration. Canonical simplifies your AI journey with long-term support and easy-to-use open-source tools. Dive into building, scaling and optimizing tools like Kubelow, MLflow, Kafka, and Spark with Canonical Data & AI solutions.

Maciej is not only the host of our podcast, but also an experienced keynote speaker. After a joint keynote at KubeconEU 2023 about highly sensitive data, in 2024, Maciej goes to Paris to talk about the GPU utilisation. During our podcast, we cover a lot of aspects of GPU utilisation. From best practices to existing tooling, there are different angles that Maciej talk about, giving a sneak-peak into his keynote. Are you curious how open source tooling plays a role in optimising the GPU utilisation? Listen to our podcast!