10% of Organizations Surveyed Launched GenAI Solutions to Production in 2023
According to the annual ML Insider survey from cnvrg.io, an Intel company, 10% of respondents said they had already launched generative AI solutions to production. (Credit: Intel Corporation)
According to the annual ML Insider survey from cnvrg.io, an Intel company, 46% of AI professionals said they considered infrastructure as the largest barrier to putting large language models into production. (Credit: Intel Corporation)
![According to the annual ML Insider survey from cnvrg.io, an Intel company, AI professionals quoted a variety of concerns regarding the implementation of large language models into their companies' business models. (Credit: Intel Corporation)]()
According to the annual ML Insider survey from cnvrg.io, an Intel company, AI professionals quoted a variety of concerns regarding the implementation of large language models into their companies' business models. (Credit: Intel Corporation)
Annual cnvrg.io survey reveals majority of organizations are still in the research and testing phase for generative AI
SANTA CLARA, Calif.--(BUSINESS WIRE)-- cnvrg.io, an Intel company and provider of artificial intelligence (AI) and large language model (LLM) platforms, today released the results of its 2023 ML Insider survey. While every industry appears to be racing toward AI, the annual survey revealed that despite interest, a majority of organizations are not yet leveraging generative AI (GenAI) technology.
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![According to the annual ML Insider survey from cnvrg.io, an Intel company, 10% of respondents said they had already launched generative AI solutions to production. (Credit: Intel Corporation)]()
According to the annual ML Insider survey from cnvrg.io, an Intel company, 10% of respondents said they had already launched generative AI solutions to production. (Credit: Intel Corporation)
Released for the third year, cnvrg.io's ML Insider survey provides an analysis of the machine learning industry, highlighting key trends, points of interest and challenges that AI professionals experience every day. This year's report offers insights from a global panel of 430 technology professionals on how they are developing AI solutions and their approaches to applying generative AI to their businesses.
"While still in early development, generative AI has been one of the most talked-about technologies of 2023. The survey suggests organizations may be hesitant to adopt GenAI due to the barriers they face when implementing LLMs," said Markus Flierl, corporate vice president and general manager of Intel Cloud Services. "With greater access to cost-effective infrastructure and services, such as those provided by cnvrg.io and the Intel Developer Cloud, we expect greater adoption in the next year as it will be easier to fine-tune, customize and deploy existing LLMs without requiring AI talent to manage the complexity."
GenAI Adoption Trends
Despite the rise in awareness of GenAI technology in 2023, it is only a slice of the overall AI landscape. The survey reveals that adoption of large language models (the models for training generative AI applications and solutions) within organizations remains low.
Three-quarters of respondents report their organizations have yet to deploy GenAI models to production, while 10% of respondents report their organizations have launched GenAI solutions to production in the past year. The survey also shows that U.S.-based respondents (40%) are significantly more likely than those outside the U.S. (22%) to deploy GenAI models.
While adoption may not have taken off, organizations that have deployed GenAI models in the past year are experiencing benefits. About half of respondents say they have improved customer experiences (58%), improved efficiency (53%), enhanced product capabilities (52%) and benefited from cost savings (47%).
Adoption Challenges
The study indicates a majority of organizations approach GenAI by building their own LLM solutions and customizing to their use cases, yet nearly half of respondents (46%) see infrastructure as the greatest barrier to developing LLMs into products.
The survey highlights other challenges that might be causing a slow adoption of LLM technology in businesses, such as lack of knowledge, cost and compliance. Of the respondents, 84% admit that their skills need to improve due to increasing interest in LLM adoption, while only 19% say they have a strong understanding of the mechanisms of how LLMs generate responses.
This reveals a knowledge gap as one potential barrier to GenAI adoption that is reflected in organizations citing complexity and lack of AI talent as the biggest barriers to AI adoption and acceptance. Additionally, respondents rank compliance and privacy (28%), reliability (23%), high cost of implementation (19%) and a lack of technical skills (17%) as the greatest concerns with implementing LLMs into their businesses. When considering the biggest challenge to bringing LLMs into production, nearly half of respondents point to infrastructure.
There is no doubt GenAI is having an impact on the industry. Compared with 2022, the use of chatbots/virtual agents has spiked 26% and translation/text generation is up 12% in 2023 as popular AI use cases. This could be due to the rise in LLM technology in 2023 and the advances in GenAI technology. Organizations that have successfully deployed GenAI in the past year see benefits from the application of LLMs, such as a better customer experience (27%), improved efficiency (25%), enhanced product capabilities (25%) and cost savings (22%).
Intel's hardware and software portfolio, including cnvrg.io, gives customers flexibility and choice when architecting an optimal AI solution based on respective performance, efficiency and cost targets. cnvrg.io helps organizations enhance their products with GenAI and LLMs by making it more cost-effective and easier to deploy large language models on Intel's purpose-built hardware. Intel is the only company with the full spectrum of hardware and software platforms, offering open and modular solutions for competitive total cost of ownership and time-to-value that organizations need to win in this era of exponential growth and AI everywhere.
For the full ML Insider 2023 report visit the cnvrg.io website.
About cnvrg.io
cnvrg.io, an Intel company, is a full-stack machine learning operating system with everything an AI developer needs to build and deploy AI on any infrastructure. cnvrg.io was built by data scientists to help data scientists and developers automate training and deployment of machine learning pipelines at scale and help organizations enhance their products with GenAI and LLMs by making it more cost-effective and easier to deploy large language models on Intel's purposebuilt hardware provided by Intel Developer Cloud. cnvrg.io helps organizations accelerate value from data science and leverage the power of generative AI technology faster.
About Intel
Intel (Nasdaq: INTC) is an industry leader, creating world-changing technology that enables global progress and enriches lives. Inspired by Moore's Law, we continuously work to advance the design and manufacturing of semiconductors to help address our customers' greatest challenges. By embedding intelligence in the cloud, network, edge and every kind of computing device, we unleash the potential of data to transform business and society for the better. To learn more about Intel's innovations, go to newsroom.intel.com and intel.com.
Intel Corporation. Intel, the Intel logo and other Intel marks are trademarks of Intel Corporation or its subsidiaries. Other names and brands may be claimed as the property of others.
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Julia Jarvis
1-469-766-7397
julia.jarvis@ketchum.com
Source: Intel
Released Dec 5, 2023 • 11:00 AM EST
10% 的受访组织在 2023 年推出了 GenAI 生产解决方案
根据英特尔公司cnvrg.io的年度ML Insider调查，有10％的受访者表示他们已经在生产中推出了生成式人工智能解决方案。（来源：英特尔公司）
根据英特尔公司cnvrg.io的年度ML Insider调查，有46％的人工智能专业人士表示，他们认为基础设施是将大型语言模型投入生产的最大障碍。（来源：英特尔公司）
![According to the annual ML Insider survey from cnvrg.io, an Intel company, AI professionals quoted a variety of concerns regarding the implementation of large language models into their companies' business models. (Credit: Intel Corporation)]()
根据英特尔公司cnvrg.io的年度ML Insider调查，人工智能专业人士列举了有关在公司商业模式中实施大型语言模型的各种担忧。（来源：英特尔公司）
cnvrg.io 年度调查显示，大多数组织仍处于生成人工智能的研究和测试阶段
加利福尼亚州圣克拉拉--（美国商业资讯）-- cnvrg.io一家英特尔公司兼人工智能 (AI) 和大型语言模型 (LLM) 平台提供商，今天发布了 2023 年 ML Insider 调查的结果。尽管每个行业似乎都在竞相向人工智能，但年度调查显示，尽管有兴趣，但大多数组织尚未利用生成式人工智能（GenAI）技术。
本新闻稿以多媒体为特色。在此处查看完整版本： https://www.businesswire.com/news/home/20231205317078/en/
![According to the annual ML Insider survey from cnvrg.io, an Intel company, 10% of respondents said they had already launched generative AI solutions to production. (Credit: Intel Corporation)]()
根据英特尔公司cnvrg.io的年度ML Insider调查，有10％的受访者表示他们已经在生产中推出了生成式人工智能解决方案。（来源：英特尔公司）
cnvrg.io的ML Insider调查连续第三年发布，对机器学习行业进行了分析，重点介绍了人工智能专业人员每天遇到的关键趋势、兴趣点和挑战。今年的报告提供了由430名技术专业人士组成的全球小组对他们如何开发人工智能解决方案以及将生成式人工智能应用于业务的方法的见解。
“虽然仍处于早期开发阶段，但生成式人工智能一直是2023年最受关注的技术之一。调查显示，由于在实施有限责任管理时面临障碍，各组织可能对采用GenAI犹豫不决。” 英特尔云服务公司副总裁兼总经理Markus Flierl说。“随着更容易获得具有成本效益的基础设施和服务，例如cnvrg.io和英特尔开发者云提供的基础设施和服务，我们预计明年将得到更多采用，因为无需人工智能人才管理复杂性即可更轻松地微调、定制和部署现有的有限责任公司。”
GenAI 采用趋势
尽管2023年人们对 GenAI 技术的认识有所提高，但它只是整个 AI 格局的一部分。调查显示，组织内部大型语言模型（用于训练生成式人工智能应用程序和解决方案的模型）的采用率仍然很低。
四分之三的受访者表示，他们的组织尚未将GenAI模型部署到生产环境中，而10％的受访者表示，他们的组织在过去一年中已将GenAI解决方案推向生产环境。调查还显示，美国的受访者（40％）部署GenAI模型的可能性要比美国以外的受访者（22％）高得多。
尽管采用率可能尚未起飞，但在过去一年中部署了GenAI模型的组织正在从中受益。大约一半的受访者表示，他们改善了客户体验（58％），提高了效率（53％），增强了产品功能（52％），并受益于成本节约（47％）。
收养方面的挑战
该研究表明，大多数组织通过构建自己的 LLM 解决方案并根据自己的用例进行定制来接触 GenAI，但将近一半的受访者（46%）认为基础设施是将 LLM 开发成产品的最大障碍。
该调查强调了可能导致企业缓慢采用法学硕士技术的其他挑战，例如缺乏知识、成本和合规性。在受访者中，有84％的人承认，由于对采用法学硕士的兴趣与日俱增，他们的技能需要提高，而只有19％的受访者表示他们对法学硕士产生回应的机制有深刻的了解。
这表明，知识差距是采用 GenAI 的潜在障碍之一，这反映在各组织将复杂性和缺乏人工智能人才列为采用和接受人工智能的最大障碍上。此外，受访者将合规性和隐私（28％）、可靠性（23％）、高实施成本（19％）和缺乏技术技能（17％）列为在业务中实施LLM的最大问题。在考虑将 LLM 投入生产的最大挑战时，将近一半的受访者指向基础设施。
毫无疑问，GenAI正在对该行业产生影响。与2022年相比，作为流行的人工智能用例，聊天机器人/虚拟代理的使用量在2023年激增了26％，翻译/文本生成量增长了12％。这可能是由于2023年法学硕士技术的兴起以及GenAI技术的进步。在过去一年中成功部署GenAI的组织看到了应用LLM的好处，例如更好的客户体验（27％）、提高了效率（25％）、增强了产品功能（25％）和节省了成本（22％）。
英特尔的硬件和软件产品组合，包括cnvrg.io，在根据各自的性能、效率和成本目标设计最佳 AI 解决方案时，为客户提供了灵活性和选择性。cnvrg.io 通过提高在英特尔专用硬件上部署大型语言模型的成本效益和便捷性，帮助组织使用 GenAI 和 LLM 增强其产品。英特尔是唯一一家拥有全方位硬件和软件平台的公司，提供开放的模块化解决方案，以实现具有竞争力的总拥有成本和价值实现时间，这是组织在指数增长和人工智能无处不在的时代中获胜所必需的。
如需完整的 ML Insider 2023 报告，请访问 cnvrg.io 网站。
关于 cnvrg.io
英特尔公司 cnvrg.io 是一款全栈机器学习操作系统，包含人工智能开发人员在任何基础设施上构建和部署人工智能所需的一切。cnvrg.io 由数据科学家构建，旨在帮助数据科学家和开发人员大规模自动化机器学习管道的训练和部署，并通过提高在英特尔开发者云提供的英特尔专用硬件上部署大型语言模型来帮助组织使用 GenAI 和 LLM 增强其产品。vrg.io 帮助组织加速实现价值来自数据科学，更快地利用生成式 AI 技术的力量。
关于英特尔
英特尔（纳斯达克股票代码：INTC）是行业领导者，致力于创造改变世界的技术，推动全球进步并丰富生活。受摩尔定律的启发，我们不断努力推进半导体的设计和制造，以帮助客户应对最大的挑战。通过将智能嵌入到云端、网络、边缘和各种计算设备中，我们释放了数据的潜力，使商业和社会变得更好。要了解有关英特尔创新的更多信息，请访问 新闻编辑室.intel.com 和 intel.com。
英特尔公司。英特尔、英特尔徽标和其他英特尔标志是英特尔公司或其子公司的商标。其他名称和品牌可能被视为他人的财产。
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朱莉娅贾维斯
1-469-766-7397
julia.jarvis@ketchum.com
来源：英特尔
2023 年 12 月 5 日发布 • 美国东部标准时间上午 11:00
