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A lot of the AI tools are cloud-native applications. Kubernetes is often used, yet professionals from the ML space lack knowledge about how to maximise its potential. From how to optimise the Kubernetes usage to how Kubernetes orchestrator simplifies the life of a data scientist, this episodes goes into the weeds of Kubernetes for AI specific use cases.

Together with Pedro Oliveira from Spectrocloud, we discussed about Kubernetes and where the future is going to look like. Listen to the latest episode, to learn more about Kubernetes and what is the role it plays in the AI use cases.

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The emergence of DevOps has changed the way enterprises handle software delivery processes, leading to faster and improved quality. After DevOps has been coined, other practices such as DataOps, MLOps, and AIOps have emerged. In the podcast, Michelle and Andreea, Data PM and AI Product Managers, respectively, will be discussing the significance of these Ops processes in streamlining and optimizing enterprise data, machine learning, and AI projects and use cases.

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Weka report from 2024 showed that 47% of respondents will use the public cloud as the primary place to develop their machine learning projects. This is a result of a correlation of factors which include the need for compute power, easy scalability, and the ability to utilise existing infrastructure already in place on both hybrid clouds and public clouds. Join us to talk more about AI on the public cloud: what are the main benefits and what are the best practices an organisation could implement in order to easier adopt AI and leverage the most the public clouds

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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!

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A special episode is out to talk about NVIDIA GTC 2024. Gustavo Sanchez will give a talk about edge AI deployments to accelerate smart city development. It will focus on how cloud native infrastructure and open source tooling enable such a project. Listed to the podcast to learn more about the use cases, challenges and key considerations for such a use case. From architectural details to possible improvements, Gustavo delights us with tons of useful information. Register now : https://register.nvidia.com/flow/nvidia/gtcs24/attendeeportal/page/sessioncatalog/session/1694086267736001Z5Wf

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Season 2 of Ubuntu AI podcast is here! After a start with great guests and great feedback from our listeners, we are ready to kickstart a new series of episodes. We will continue talking about AI and open source, focusing mostly on the machine learning lifecycle, AI on public cloud, AI at the edge and the security angle of the AI projects. This time around, we will periodically invite contributors to open source projects from the AI space to join us. Stay tuned, great times are ahead of us!

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In this episode, we delve into the intricate world of AI regulations. As artificial intelligence continues to revolutionize various industries, the need for comprehensive regulations becomes increasingly apparent. Join us as we navigate through the complexities of AI governance, discussing the current state of regulations, the challenges faced by policymakers, and the implications for businesses and society at large.

In this episode we host Juan Luis Cano Rodrigues, Principal Product Manager at QuantumBlack, AI by McKinsey.

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In this episode we're talking with the founder of Nextcloud Frank Karlitschek, whom we met during the Ubuntu Summit 2023 in Riga.
We'll dive deeper into the usage of AI in Nextcloud. Learn where, how and why AI solutions are implemented there. 

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Secure and automate the deployment, maintenance and upgrades of Spark on Kubernetes. Run your big data clusters across private and public clouds.

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