Recently, the third Knowledge Graph Industry Development Forum and Knowledge Graph and Large Model Integration Seminar were held in Beijing. At the meeting, the "Research Report on the Integration of Knowledge Graph and Large Model Practice" was officially released!
This white paper was jointly published by the China Electronics Technology Standardization Institute, relying on the Knowledge Graph Industry Promotion Array, the Knowledge Graph Working Group of the Artificial Intelligence Subcommittee of the National Beacon Committee, and 32 enterprises, institutions, universities and research institutes. "Integration Practice Research Report" was released, and Chuanglin Technology participated in the editing. "Knowledge Graph and Large Model Integration Practice Research Report" was released, and Chuanglin Technology participated in the editing.
As a leading company in graph databases, Chuanglin Technology participated in the preparation of the "Research Report on the Integration of Knowledge Graphs and Large Models" and shared the direction of combining knowledge graphs and large models.
Starting from the bottlenecks faced by the implementation of knowledge graphs and large models, the research report analyzes the main characteristics of knowledge graphs and large models, the main scenarios and core basic capabilities that knowledge graphs and large models are good at, and compares the advantages and disadvantages of knowledge graphs and large models. Then the feasibility and benefits of integrating knowledge graphs and large models were discussed from the perspective of technological evolution, technological complementarity, and knowledge base construction.
At the same time, the research report also analyzes the technical path and key technologies for the integration of knowledge graphs and large models.
From the perspective of knowledge graphs, the report proposes to use the technical advantages of large models in semantic understanding, content generation and other aspects to realize the enhancement of large models in all aspects of the entire life cycle from knowledge graph construction to application, and improve efficiency and quality. For large models, the advantages of knowledge graphs in knowledge standardization, interpretability, credibility, traceability, etc. can enhance the multiple links of large models from pre-training to application, and improve the training effect and reasoning of large models. Availability of results.
On the basis of mutual empowerment, the interconnection between knowledge graphs and integrated scheduling between large models are used to continuously enhance the capabilities of the integrated system through technical means such as unified knowledge representation and dynamic collaborative knowledge reasoning, and achieve enterprise-level recognition. Upgrading and development of decision-making intelligence level.
The official release of the "Research Report on the Integration of Knowledge Graphs and Large Models" can help enterprises correctly select, implement and apply knowledge graphs, and promote the in-depth integration and application of knowledge graphs in various fields.
At present, as the leading graph database manufacturer in China, Chuanglin Technology is also leveraging its deep accumulation and application in knowledge graph construction and application to take the lead, actively practice the integration of domestic graph databases and large models, and conduct testing and testing in the financial field where it is good at Research, through the most realistic practical data and experience, promotes the application of the integration of knowledge graphs and large models in the industry, providing support for releasing the greater value of graph technology and accelerating the integrated application of graph technology in various fields.