After Open AI released the GPT large model in 2022, there was a boom in AI entrepreneurship, but investment cooled down. This article analyzes the reasons behind this phenomenon and puts forward corresponding suggestions. A large number of AI startups have flooded into the market, but most of them have slow commercialization processes and are difficult to attract investment. At the same time, investors are cautious in facing the massive number of AI projects, and very few projects have actually received investment. In addition, the serious shortage of core talents in the AI field has also become an important factor restricting the implementation of projects.
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After the release of Open AI's GPT large model in November 2022, the AI entrepreneurship craze continued to rise, but data shows that the scale of investment and financing in the AI field is declining. The reason is that on the one hand, there are a large number of AI entrepreneurial teams but the commercialization process is slow and it is difficult to obtain investor recognition; on the other hand, investors receive a large number of AI concept business plans but few actual projects are launched, and there is a serious shortage of core talents in the AI field. , these all restrict the implementation of the project. The article suggests that investors should carefully select AI teams with market validation and increase efforts in talent training.
To sum up, although the investment boom in the AI field continues, it faces challenges such as slow commercialization, talent shortage, and investor caution. In the future, the development of the AI industry needs to pay more attention to practical applications and talent training in order to achieve sustainable development. Investors need to be more rational, choose projects with market competitiveness, and avoid blindly following the trend.