根据英特尔公司旗下专注于 AI 和大型语言模型（LLM）平台的 cnvrg.io 进行的 2023 年 ML Insider 调查显示，过去一年中只有 10% 的企业组织将生成式 AI（GenAI）解决方案整合到生产中。
这一调查结果揭示了一个令人惊讶的事实：尽管生成式 AI 技术在过去几年中取得了巨大的进展，但在实际应用场景中，其普及率仍然相对较低。这可能表明，许多企业在采用新技术方面仍然持谨慎态度，或者他们尚未找到将生成式 AI 技术与自身业务相结合的有效方法。
生成式 AI 技术具有巨大的潜力，可以帮助企业提高生产效率、降低成本、改善客户体验等。然而，要充分利用这些潜力，企业需要克服一些挑战，包括技术成熟度、数据安全和隐私保护等问题。
此外，培训员工以适应新技术也是一个重要问题。随着生成式 AI 技术的不断发展，员工需要掌握新的技能和知识，以便更好地利用这些技术来提高工作效率。
英语如下：
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“News Headline: Only 10% of Enterprises Adopt Generative====
“News Headline: Only 10% of Enterprises Adopt Generative AI, the Path to Technological Popularization is Long
Keywords: AI Application, Enterprise Adoption, Production Integration
News Content: According to the 2023 ML Insider survey conducted by cnvrg.io, a subsidiary of Intel Corporation focusing on AI and large language model (LLM) platforms, only 10% of enterprise organizations have integrated generative AI (GenAI) solutions into their production in the past year.
This survey result reveals a surprising fact: despite the significant progress made by generative AI technology in the past few years, its adoption rate in practical application scenarios remains relatively low. This may indicate that many enterprises still hold a cautious attitude towards adopting new technologies or they have not yet found an effective way to combine generative AI technology with their own business.
Generative AI technology has enormous potential to help enterprises improve production efficiency, reduce costs, and enhance customer experience. However, to fully leverage these potentials, enterprises need to overcome some challenges, including issues related to technological maturity, data security, and privacy protection.
In addition, training employees to adapt to new technologies is also an important issue. With the continuous development of generative AI technology, employees need to acquire new skills and knowledge so that they can better utilize these technologies to improve work efficiency.”
【来源】https://www.ithome.com/0/737/399.htm
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