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

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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

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本文主要介绍了LLMOps(大型语言模型运营)的概念、重要性以及DataRobot如何提供LLMOps解决方案。LLMOps是MLOps(机器学习运营)的一个子集,专门针对大型语言模型的独特挑战和需求。文章指出,随着生成式AI(GenAI)的投资增加,组织需要确保其生成式AI投资能够产生实际价值,并保护公司声誉。LLMOps能够帮助组织管理、监控和治理其生成式和预测式AI资产,确保AI/ML模型在生产中的可靠性、可扩展性和安全性。文章还提到,DataRobot的LLMOps解决方案能够提供性能监控、运营监控、信任监控和治理,帮助组织在单一平台上管理、监控和治理所有生成式和预测式AI资产。
什么是LLMOps,它与MLOps有何不同? 为什么组织需要LLMOps和MLOps一起使用? DataRobot如何帮助组织实现有效的LLMOps和MLOps?
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