Chinese users actively deploy generative AI technology, accounting for 26% - Gartner survey report

News on May 23, according to a report by Sun Xin Risk, research director of market research firm Gartner, Chinese users have made certain progress in the deployment of generative AI technology. As of now, about 26% of Chinese users have begun to deploy generative AI technology.

The report pointed out that in China, 6% of users have successfully deployed technology related to generative AI, and 26% of users are actively piloting this technology. In addition, about a quarter (24%) of users stated that they plan to adopt applications or technologies related to generative artificial intelligence in the next 0-6 months. China leads Southeast Asia and the Middle East in the field of generative AI, with the latter having only 3% of users.

In Sun Xin’s view, Chinese users generally trust the data-centered generative artificial intelligence capabilities, which are generally better than model-centered artificial intelligence methods.

Gartner's "2022 Artificial Intelligence Technology Hype Cycle" report points out that the early adoption of AI technologies such as compound artificial intelligence and decision intelligence will bring obvious competitive advantages to enterprise organizations and alleviate the vulnerability of AI models. questions and help capture business background information to drive value realization. According to ITBEAR technology information, Gartner believes that a popular technical capability that may emerge in the future is so-called "responsible AI", which adds a layer of insurance to generative AI to process generated content in a responsible manner.

From the perspective of technology trends, Sun Xin said that it can be interpreted from the following three aspects:

First, from the architectural perspective, the current mainstream generation Modern AI applications often run on the cloud, but in regulated industries, enterprises may increasingly choose to deploy on-premises. This move could not only increase the value of hardware for infrastructure providers, but also effectively leverage the capabilities of generative AI.

In addition, more large models and Fine-Tuning models will be launched in the future. The advantage of the Fine-Tuning model is that it can more accurately adapt to business scenarios, thereby reducing costs and improving matching. In this system, open source software and open source communities will play an important role.

Finally, from the operational perspective, the next six months may see “prompt engineering” become an important market trend, while “vector database” will play a key role on the operational side.

With the development of generative artificial intelligence technology, enterprises are also facing some potential risks that need to be paid attention to. Generative AI products face some risks and challenges, as revealed by some negative news about ChatGPT. Therefore, ITBEAR Technology Information reminds users that when using current generative artificial intelligence products, they should treat them with a responsible attitude and not blindly follow trends.

In China, certain progress has been made in the deployment of generative AI technology. However, this does not mean that the deployment process is risk-free. Ensuring that content generated by generative AI complies with ethical and legal standards is a significant challenge for businesses. Overreliance on generative AI may also lead to misleading and out-of-control artificial intelligence.

When using generative AI technology, both enterprises and users should maintain a prudent and responsible attitude, and not only enjoy the convenience and innovation brought by the technology. For enterprises, it is crucial to establish effective supervision and audit mechanisms. In addition, governments and regulatory agencies need to strengthen supervision and guidance on generative AI technology to ensure that it can be developed in compliance with ethical and legal frameworks.

In short, generative AI technology has been recognized and deployed to a certain extent among Chinese users. However, with this comes potential risks and challenges. Enterprises and users should work together to advance the development of self-generated AI technology in a responsible manner and ensure that it meets social and ethical expectations.

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