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MLOps is alive and well (Practical AI #210)
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MLOps Engineer - What Do You Think Will Be Next?
Daniel: We're used to being just like the luntously resourced in the cloud, you know, everything you could possibly want there. And yet we have this incredible diversity. How does MLOps look when you're talking about diversity of use cases plus diversity of users and that you're serving? You know, how do you keep it all together there? Daniel: There's enough stuff that we still need to solve that will probably be around both Kubernetes and prompt engineering. But I don't see that going away anytime soon as long as there's a machine learning system.
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