Research on Knowledge Creation and Innovation Method based on Deep Learning and Human-machine Collaboration Model

Abstract

Knowledge creation and innovation have reached a stage of high-quality development since the widespread application of deep learning and human-machine collaboration models. Proposing better theoretical propositions to meet knowledge creation and innovation needs in the knowledge economy is necessary by adhering to knowledge-driven innovation ideas. Based on the dynamic evolution of deep learning and human-machine collaboration model development, a theoretical analysis framework for the sustainable development of the knowledge industry is constructed according to the inherent logic of knowledge creation and innovation, which can explain the knowledge creation and innovation development mechanism jointly generated by the knowledge generation mechanism and knowledge circulation mechanism involving deep learning and human-machine collaboration mode. And continue to explore the possibility of moving towards the goal of high-quality knowledge development from the perspective of challenges, changes, and practical deductions in the development of the knowledge industry. Knowledge creation and innovative development aim to provide content that meets expected standards for the knowledge economy and is committed to continuously improving knowledge quality and enhancing knowledge satisfaction. Therefore, it is necessary to strengthen knowledge control based on the deep learning quality internal cycle, build an interaction and feedback mechanism between human-machine collaboration mode and knowledge quality perception, and establish a knowledge and economic evaluation system to achieve knowledge creation and innovate high-quality development, promote knowledge economy, and truly meet social needs.