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Generative AI reshapes the knowledge value chain

** Generative AI has brought new vitality to the knowledge value chain with its powerful language understanding and generation capabilities. It can extract valuable information from massive amounts of data and present it in a novel and easy-to-understand way. For example, in the field of education, generative AI can generate personalized learning plans and tutoring materials based on students' learning situations and characteristics, greatly improving the utilization efficiency of educational resources. In the field of scientific research, it can help researchers quickly sort out and summarize research results in related fields, and provide inspiration and enlightenment for new research directions. By analyzing and understanding a large amount of literature, generative AI can discover potential research hotspots and trends, saving researchers a lot of time and energy. **

Insights and Exchanges at the World Artificial Intelligence Conference

** The World Artificial Intelligence Conference brought together the world's top experts, scholars and business representatives, providing an excellent platform for discussing the impact of generative artificial intelligence on the knowledge value chain. At the conference, all parties shared the latest research results and application cases, and jointly discussed future development directions. Participants generally believed that generative artificial intelligence has not only changed the way knowledge is acquired and disseminated, but also had a profound impact on the innovation and application of knowledge. At the same time, some people are concerned about the ethical and legal issues that generative artificial intelligence may bring, such as the protection of intellectual property rights and the spread of false information. **

The importance and challenges of posting projects and finding people

** In this context, the model of "posting projects and finding people" came into being. It aims to accurately match projects with talents with corresponding capabilities, and improve the success rate and efficiency of projects. However, this model also faces many challenges. First of all, how to accurately describe project requirements and talent skills to achieve accurate matching is a key issue. Project requirements may involve multiple fields and complex technical requirements, and the skills and experience of talents are also diverse and complex. Therefore, it is necessary to establish a scientific and effective description and evaluation system. Secondly, the authenticity and reliability of information is also an issue that cannot be ignored. In the process of "posting projects and finding people", there may be false information, exaggerated propaganda, etc., which will not only waste the time and energy of both parties, but may also lead to the failure of the project. Furthermore, since it involves the flow of talents and cross-regional cooperation, relevant legal, policy and cultural differences need to be resolved. Differences in laws, regulations, tax policies, work visas, etc. in different regions may bring obstacles to the implementation of the project. **

Response strategies and future prospects

** In order to meet these challenges, we can adopt a series of strategies. Strengthen the supervision and review mechanism of the platform to ensure the authenticity and reliability of information. At the same time, use big data and artificial intelligence technology to continuously optimize the matching algorithm and improve the accuracy of matching. Strengthen cross-field cooperation and communication, and cultivate compound talents who understand both technology and business to better understand project needs and talent skills. In addition, the government and relevant agencies should also introduce corresponding policies and regulations to create a good environment for the development of the "post project to find people" model. Looking to the future, with the continuous development and improvement of generative artificial intelligence, the "post project to find people" model is expected to play an important role in more fields. It will not only promote the further optimization and upgrading of the knowledge value chain, but also bring more opportunities and possibilities for the development and progress of society. We have reason to believe that under the guidance of science and technology, the future world will be better. In short, the trend of generative artificial intelligence to reshape the knowledge value chain is unstoppable. The World Artificial Intelligence Conference provides us with a platform for thinking and communication, and the "post project to find people" model is an important way for us to actively respond to challenges and seize opportunities in this change. Let us look forward to a smarter and more innovative future together!