DataRobot：2024年LLMOps（大语言模型运营）：生成式AI策略的基础白皮书（英文版）（12页）.pdf

1、Everything You Need to Know About LLMOpsWHITE PAPERThe Foundation for Your Generative AI StrategyIntroductionGenerative AI(GenAI)is a very hot topic.As organizations try to seize the opportunity,investments in generative AI are on the rise,which will further accelerate the adoption of technologies i

2、n this niche.Todays AI leaders need to showcase tangible value from their generative AI investments and ensure theyre protecting their companys reputation given the potential pitfalls,like the risk for generative AI to return inaccurate answers or lack of trust in generative AI outputs.In this envir

3、onment,many organizations are bound to end up with a“frankenstein”infrastructure,as teams try out new technologies,experiment,and introduce new capabilities.This has the potential to quickly spiral out of control,exacerbate technical debt,increase upkeep,and drive costs through the roof.At best,the

4、path to actual business value becomes murky under these circumstances.The only tangible way to prevent this from happening is to ensure that generative AI solutions are properly monitored,maintained,and governed,which is impossible to do without a single system of record that creates the necessary p

5、rocedural and technical guardrails.For predictive AI,the collection of these processes,guardrails,and integrations is often referred to as MLOps.But generative AI has its own unique challenges,which should be addressed accordingly with LLMOps,a subset of MLOps,tailored to large language models(LLMs)

6、unique challenges and requirements.HAVE PRIORITIZED IT FOR INVESTMENT THROUGH 2025*OF IT DECISION MAKERS HAVE PRIORITIZED GENERATIVE AI FOR INVESTMENT IN 202359%66%*GlobalData,Generative AI Watch:DataRobots Platform Upgrades Address Top Enterprise Challenges,20231WHITE PAPER|10 Key Considerations fo