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.
View source version on businesswire.com: https://www.businesswire.com/news/home/20231205317078/en/
Julia Jarvis
1-469-766-7397
julia.jarvis@ketchum.com
Source: Intel
Released Dec 5, 2023 • 11:00 AM EST
10% 的受訪組織在 2023 年推出了 GenAI 生產解決方案
根據英特爾公司cnvrg.io的年度ML Insider調查，有10％的受訪者表示他們已經在生產中推出了生成式人工智能解決方案。（來源：英特爾公司）
根據英特爾公司cnvrg.io的年度ML Insider調查，有46％的人工智能專業人士表示，他們認爲基礎設施是將大型語言模型投入生產的最大障礙。（來源：英特爾公司）
![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)]()
根據英特爾公司cnvrg.io的年度ML Insider調查，人工智能專業人士列舉了有關在公司商業模式中實施大型語言模型的各種擔憂。（來源：英特爾公司）
cnvrg.io 年度調查顯示，大多數組織仍處於生成人工智能的研究和測試階段
加利福尼亞州聖克拉拉--（美國商業資訊）-- cnvrg.io一家英特爾公司兼人工智能 (AI) 和大型語言模型 (LLM) 平台提供商，今天發佈了 2023 年 ML Insider 調查的結果。儘管每個行業似乎都在競相向人工智能，但年度調查顯示，儘管有興趣，但大多數組織尚未利用生成式人工智能（GenAI）技術。
本新聞稿以多媒體爲特色。在此處查看完整版本： 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)]()
根據英特爾公司cnvrg.io的年度ML Insider調查，有10％的受訪者表示他們已經在生產中推出了生成式人工智能解決方案。（來源：英特爾公司）
cnvrg.io的ML Insider調查連續第三年發佈，對機器學習行業進行了分析，重點介紹了人工智能專業人員每天遇到的關鍵趨勢、興趣點和挑戰。今年的報告提供了由430名技術專業人士組成的全球小組對他們如何開發人工智能解決方案以及將生成式人工智能應用於業務的方法的見解。
“雖然仍處於早期開發階段，但生成式人工智能一直是2023年最受關注的技術之一。調查顯示，由於在實施有限責任管理時面臨障礙，各組織可能對採用GenAI猶豫不決。” 英特爾雲服務公司副總裁兼總經理Markus Flierl說。“隨着更容易獲得具有成本效益的基礎設施和服務，例如cnvrg.io和英特爾開發者雲提供的基礎設施和服務，我們預計明年將得到更多采用，因爲無需人工智能人才管理複雜性即可更輕鬆地微調、定製和部署現有的有限責任公司。”
GenAI 採用趨勢
儘管2023年人們對 GenAI 技術的認識有所提高，但它只是整個 AI 格局的一部分。調查顯示，組織內部大型語言模型（用於訓練生成式人工智能應用程序和解決方案的模型）的採用率仍然很低。
四分之三的受訪者表示，他們的組織尚未將GenAI模型部署到生產環境中，而10％的受訪者表示，他們的組織在過去一年中已將GenAI解決方案推向生產環境。調查還顯示，美國的受訪者（40％）部署GenAI模型的可能性要比美國以外的受訪者（22％）高得多。
儘管採用率可能尚未起飛，但在過去一年中部署了GenAI模型的組織正在從中受益。大約一半的受訪者表示，他們改善了客戶體驗（58％），提高了效率（53％），增強了產品功能（52％），並受益於成本節約（47％）。
收養方面的挑戰
該研究表明，大多數組織通過構建自己的 LLM 解決方案並根據自己的用例進行定製來接觸 GenAI，但將近一半的受訪者（46%）認爲基礎設施是將 LLM 開發成產品的最大障礙。
該調查強調了可能導致企業緩慢採用法學碩士技術的其他挑戰，例如缺乏知識、成本和合規性。在受訪者中，有84％的人承認，由於對採用法學碩士的興趣與日俱增，他們的技能需要提高，而只有19％的受訪者表示他們對法學碩士產生回應的機制有深刻的了解。
這表明，知識差距是採用 GenAI 的潛在障礙之一，這反映在各組織將複雜性和缺乏人工智能人才列爲採用和接受人工智能的最大障礙上。此外，受訪者將合規性和隱私（28％）、可靠性（23％）、高實施成本（19％）和缺乏技術技能（17％）列爲在業務中實施LLM的最大問題。在考慮將 LLM 投入生產的最大挑戰時，將近一半的受訪者指向基礎設施。
毫無疑問，GenAI正在對該行業產生影響。與2022年相比，作爲流行的人工智能用例，聊天機器人/虛擬代理的使用量在2023年激增了26％，翻譯/文本生成量增長了12％。這可能是由於2023年法學碩士技術的興起以及GenAI技術的進步。在過去一年中成功部署GenAI的組織看到了應用LLM的好處，例如更好的客戶體驗（27％）、提高了效率（25％）、增強了產品功能（25％）和節省了成本（22％）。
英特爾的硬件和軟件產品組合，包括cnvrg.io，在根據各自的性能、效率和成本目標設計最佳 AI 解決方案時，爲客戶提供了靈活性和選擇性。cnvrg.io 通過提高在英特爾專用硬件上部署大型語言模型的成本效益和便捷性，幫助組織使用 GenAI 和 LLM 增強其產品。英特爾是唯一一家擁有全方位硬件和軟件平台的公司，提供開放的模塊化解決方案，以實現具有競爭力的總擁有成本和價值實現時間，這是組織在指數增長和人工智能無處不在的時代中獲勝所必需的。
如需完整的 ML Insider 2023 報告，請訪問 cnvrg.io 網站。
關於 cnvrg.io
英特爾公司 cnvrg.io 是一款全棧機器學習操作系統，包含人工智能開發人員在任何基礎設施上構建和部署人工智能所需的一切。cnvrg.io 由數據科學家構建，旨在幫助數據科學家和開發人員大規模自動化機器學習管道的訓練和部署，並通過提高在英特爾開發者雲提供的英特爾專用硬件上部署大型語言模型來幫助組織使用 GenAI 和 LLM 增強其產品。vrg.io 幫助組織加速實現價值來自數據科學，更快地利用生成式 AI 技術的力量。
關於英特爾
英特爾（納斯達克股票代碼：INTC）是行業領導者，致力於創造改變世界的技術，推動全球進步並豐富生活。受摩爾定律的啓發，我們不斷努力推進半導體的設計和製造，以幫助客戶應對最大的挑戰。通過將智能嵌入到雲端、網絡、邊緣和各種計算設備中，我們釋放了數據的潛力，使商業和社會變得更好。要了解有關英特爾創新的更多信息，請訪問 新聞編輯室.intel.com 和 intel.com。
英特爾公司。英特爾、英特爾徽標和其他英特爾標誌是英特爾公司或其子公司的商標。其他名稱和品牌可能被視爲他人的財產。
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朱莉婭賈維斯
1-469-766-7397
julia.jarvis@ketchum.com
來源：英特爾
2023 年 12 月 5 日發佈 • 美國東部標準時間上午 11:00
