
Ubuntu AI | Ep 4: Canonical AI roadshow
09/14/23 • 30 min
What is Canonical AI roadshow? Well, basically we are trying to meet the community that is working with us and people that are contributing to the projects that we are open sourcing and we decided to go to a couple of different places all around the globe to be able to meet all the partners that we have, to meet the people engaged with us on different projects and also to basically promote an open access to innovation with what we do.
Check rest here: https://ubuntu.com/ai/roadshow
Learn more about our solutions here: https://ubuntu.com/ai
What is Canonical AI roadshow? Well, basically we are trying to meet the community that is working with us and people that are contributing to the projects that we are open sourcing and we decided to go to a couple of different places all around the globe to be able to meet all the partners that we have, to meet the people engaged with us on different projects and also to basically promote an open access to innovation with what we do.
Check rest here: https://ubuntu.com/ai/roadshow
Learn more about our solutions here: https://ubuntu.com/ai
Previous Episode

Ubuntu AI | Ep 3: What is MLOps?
What's MLOps, you ask? It's the magical synergy between Machine Learning and DevOps, and it's changing the game for businesses worldwide. From model development and deployment to monitoring and maintenance, MLOps is the backbone of seamless, efficient, and scalable AI systems.
In this episode we talk about one of the most trending topics of 2023 - MLOps.
Tune in and learn: what is MLOps, how to get started with MLOps, what are the major use-cases and how you can start integrating MLOps in your organization?
The podcast is hosted by Andreea (MLOps Product Manager) and Maciej (Principal of AI/ML) from Canonical.
Learn more about our solutions here: https://ubuntu.com/ai
Next Episode

Ubuntu AI | Ep 5: Understanding MLOps and Observability
In this episode we're hosting Simon Aronsson, Senior Engineering Manager for Canonical Observability Stack.
Machine learning operations (MLOps) is a new practice that ensures ML workflow automation in a scalable and efficient manner. But how do you make MLOps observable? How can you better understand how your product-grade AI initiative and its infrastructure are performing?
This is where observability comes in.
Learn more about our solutions here: https://ubuntu.com/ai
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