Shulou(Shulou.com)11/24 Report--

CTOnews.com May 23 news, according to market research firm Gartner Research Director Sun Xin risk report, shows that about 26% of Chinese users have begun to deploy generative AI technology.

The survey results also show that 6% of users in China have successfully deployed technologies related to generative AI, 26% of users are actively piloting generative AI technology, and about 24% of Chinese users say they will deploy spanning AI-related applications or technologies in the next 0-6 months. The proportion of users who have no plan recently or will not have a plan until five or six months later is about 14%. By contrast, 3% in Southeast Asia and the Middle East, with Chinese users relatively ahead of the comparison.

Sun Xin believes that Chinese users are more confident in the generative AI ability of data-centered (Data-Centric AI), and their overall confidence is higher than some other types, such as model-centered (Model-Centric) AI.

According to the report of Gartner "2022 artificial Intelligence Technology maturity Curve", the early adoption of AI technologies such as compound artificial Intelligence (AI) and decision Intelligence will bring obvious competitive advantages to enterprises, alleviate the problems caused by the fragility of AI models, and help to capture business background information and promote value realization. Gartner believes that the next wave of hot technical capabilities may be the so-called "responsible AI." That is, to add an insurance on the generative AI to minimize the "illusion" of the content produced by the generative AI and to deal with it in a responsible way. With regard to the technological trend of future generative AI, Sun Xin said that it can be interpreted from the following three angles:

From an architectural point of view, the mainstream is still running on the cloud or using generative AI applications, but in some regulated industries, there may be a surge in internal choices, and you may see some local deployment options. For infrastructure vendors, some of the added value of their hardware can be realized through the ability to generate AI.

Model itself, the introduction of large models will be more and more, and there will be more Fine-Tuning models in the future. The advantage of the Fine-Tuning model is that it has a higher degree of matching and is closer to the business scenario, which means lower cost. Open source software or the open source community will play an important role in this system.

From an operational point of view, the "prompt project" may become a very important market in the next 6 months, while the "vector database" will become very important on the operational side.

Under the premise of generative AI technology, generative AI technology will also potentially bring some risks to enterprises. This has been reflected in some of the "negative" news on ChatGPT, with CTOnews.com reminding that current generative artificial intelligence products should be treated and used in a responsible manner and should not blindly follow suit.

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