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生成式 AI:炒作与现实的结合 新一波AI浪潮已经出现.pdf

上传人: le****ng 编号:187000 2024-12-17 27页 13.32MB

1、Generative AI:Hype meets RealityMohannad AbuissaCTO-Cisco Middle East&AfricaTurkey,Romania and CiSCisco ConfidentialScarcityAbundanceCisco Confidential8 BILLION80 BILLIONCisco ConfidentialPublic&Private Data CentersAI-Ready Data CentersEvolving Apps&InfrastructureFoundation for Generative AI Reality

2、Cisco ConfidentialCisco AI Readiness Index 2024Foundational Technologies-LLM/deep learning/automationCompanies that leverage foundational technology to build products and services Businesses deploying these AI powered services to achieve specific outcomesEnd users HypeThe Real Impact1234AI:Hype vs R

3、ealityWhat we set out to achieveMeasure ReadinessAddress Gaps in readinessWhat challenges,if any,they are facing as they address these?Current and future ROI on AI InvestmentsStrategyInfrastructureDataTalentGovernanceCultureThe foundational building blocksAI Readiness:Feel that urgency to deploy AI/

4、AI-powered technologies has increased in the past six months98%Companies say CEO and the leadership team are top drivers of urgency to deploy AI50%The urgency to deploy AI continuesAI Readiness:The CEO and the Leadership team are driving the urgency,closely supported by the Board of Directors and Bu

5、siness Unit Leaders.Global AI Readiness is flatlining/decliningCompanies are investing,but gains arent meeting expectationsThe pressure to succeed is relentlessKey takeawaysAI Readiness:Limited PreparednessGlobal AI Readiness1%23%48%28%6%48%31%15%15%43%29%13%9%49%26%16%6%46%33%16%17%43%32%9%3%51%33%

6、13%OverallStrategyInfrastructureDataGovernanceTalentCultureUnpreparedModerate PreparednessFully PreparedGap85%59%13%Between urgency and ability is especially startlingFeel they have 18 months to show value or lose competitive advantage59%give it only 12 monthsOf companies are fully ready to capture

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本文讨论了生成式人工智能(AI)的现实与炒作之间的差距,并强调了构建生成式AI所需的基础技术,如大型语言模型、深度学习和自动化。研究指出,尽管公司正在投资AI,但投资回报并未达到预期。全球AI准备指数呈平稳或下降趋势,只有少数公司认为自己在AI准备方面处于领先地位。公司面临的挑战包括数据中心的网络设备无法满足AI工作负载需求、缺乏人才、网络安全风险以及长期交货时间。为了提高AI准备度,文章建议组织应进行长期规划,建设未来导向的基础设施,打破数据孤岛,制定及时的内部政策和协议,并优化AI模型。此外,文中还提到了Cisco的一些产品,如与NVIDIA合作的AI集群、Cisco 6000系列交换机和Nexus Hyperfabric,以及基于Cisco Silicon One和Optics创新的NVIDIA GPU/DPU/NIC BlueField-3等,旨在促进AI的民主化并加速其在企业中的应用。
炒作还是实质?" "如何在企业中提升AI准备度?" 期望与现实差距?"
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