Data Collection and Preprocessing
Obtain publicly available datasets from quantum computing, bioengineering, and materials science, and use GPT-4 for data cleaning and annotation..
Model Training and Optimization
Build an interdisciplinary knowledge graph through GPT-4 fine-tuning to enhance the model’s understanding of specific domains.
Experimentation and Validation
Test the model’s performance in quantum algorithm optimization, gene editing experiments, and material screening, comparing it with traditional methods.
Expected outcomes include
Enhancing GPT-4’s application capabilities in interdisciplinary fields, providing new insights for the integration of AI and cutting-edge technologies.
Validating the practical value of AI in quantum computing, bioengineering, and materials science, driving technological breakthroughs in these areas.
Offering more efficient solutions for society, such as accelerating drug development and optimizing energy materials, promoting technological progress and economic growth.
