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Inside Big Data: Heard on the Street – 9/26/2023


“For years, MLOps has operated under the assumption that traditional models are a bespoke thing when, in fact, models are just code + data. And throwing MLOps into the mix rather than just aligning with DevOps has only added unnecessary complexity.

But large language models (LLMs) are a different beast, hence the emergence of LLMOps. LLMs have nuances that call for a new set of best practices to build, deploy, and maintain these specialized models. LLMs models are like cloud services, microservices and APIs. They need to be chained together to form an application. But how do you achieve this while making these models behave the way you want them to? This is giving rise to questions around prompt management and model quality. 

Read the full article on Inside Big Data Here 

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