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“better practices like MLOps, LLMOps”

Umm, what do these practices entail exactly? MLOps I can guess, but I think is probably of questionable utility, and certainly not a mature enough practice to outright assume it’s “better” than existing practices.

LLMops I hadn’t heard of, but it sounds like a really bad idea.

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Here's a reasonable post by nvidia that can help put the terms in context (take it with a grain of salt given the marketing overtones) https://developer.nvidia.com/blog/mastering-llm-techniques-l... .

MLOps is akin to DevOps but takes into account getting machine learning models to production and how to instill a process so that you can iterate and avoid outages, etc.

“What Is LLMOps?” https://www.databricks.com/glossary/llmops

I was equally wary because I assumed a similarity to “ChatOps” but, in fact, MLOps and LLMOps are about operating ML/LLM services, not using them to automate ops.

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