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电信管理论坛(TMF):2024通信服务提供商(CSPs)如何利用生成式AI建立和维护大型语言模型(LLMs)(中译版)(25页).pdf

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1、Author:Dean Ramsay,Principal Analyst Editor:Ian Kemp,Managing EditorSponsored by:labsknowledgecode+frameworkstraining+accreditationimplementing GenAIhow to set up and maintain large language models2contents03 setting the scene05 chapter 1:what is a GenAI large language model(LLM)?07 chapter 2:settin

2、g up telecoms LLMs12 chapter 3:maintenance of LLMs15 chapter 4:evolving standards for AI17 additional feature from Tata Consultancy Services 23 meet the Research and Media team 23The creation and integration of generative AI(GenAI)models into telcos business processes is a complex undertaking.As com

3、munications service providers(CSPs)move from proof-of-concept projects to live deployments it is becoming clear that constructing the right language model is key to success.Some CSPs are setting out to develop large language models(LLMs)specifically for the telecoms industry as we have outlined in o

4、ur benchmark report,Building an AI strategy:telcos put the foundations in place.The Global Telco AI Alliance,for example whose founders are e&,Deutsche Telekom,Singtel,SK Telekom and Softbank aims to develop multilingual LLMs for operator businesses globally.Our recent survey compiled for our benchm

5、ark report and its sister report Generative AI:operators take their first steps shows that CSPs are expecting a significant impact on their businesses in the short term from implementing GenAI/LLMs.setting the sceneWhen do you expect that GenAI/LLMs willhave a significant impact on your business?TM

6、Forum,2023More than 5 yearsBetween 2 and 5 yearsOver the next 1-2 years57%37%6%4 4In this e-book we look at the typical processes that CSPs are adopting to set up large language models and how they intend to maintain them.For our research we interviewed several progressive CSPs to establish current

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本文主要讨论了生成式人工智能(GenAI)在电信行业中的大型语言模型(LLM)的设置和维护。文章首先介绍了GenAI和LLM的概念,然后详细阐述了设置LLM的七个步骤,包括模型架构设计、数据收集和格式化、优化标记化、训练LLM、评估、微调和专业化、部署和用户交互。接着,文章讨论了LLM维护的几个关键考虑因素,包括性能监控、内容数据管理、伦理考量、安全和可扩展性。此外,文章还强调了合作和标准的重要性,并介绍了TM Forum在推动完全AI启用的开放数字架构方面的努力。最后,文章通过Tata Consultancy Services的额外内容,提供了一个GenAI生产路径的框架,包括价值链分析、系统和人机领域热点识别、热点评估、风险评估和分类以及生产扩展所需的AI优先企业架构。
什么是生成式AI大语言模型? 如何设置和维护大语言模型? 生成式AI大语言模型对电信业务有何影响?
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