Core Insights - The article discusses the integration of AI technology in agricultural breeding, specifically through the "Fengdeng" project, which aims to enhance crop breeding efficiency and precision using AI models [1][2]. Group 1: AI in Agricultural Breeding - The "Fengdeng" project, launched by a collaborative team including Shanghai Artificial Intelligence Laboratory and other research institutions, introduced the "Fengdeng·Seed Industry Large Model" in April 2024, followed by the "Fengdeng·Gene Scientist" AI tool in July 2024, designed to assist researchers in exploring and validating unknown gene functions [1]. - Traditional breeding methods are time-consuming and heavily reliant on expert experience, often taking years to validate hypotheses with limited success rates [1]. - The AI model is trained on vast datasets to identify relationships between genes and traits, enabling it to predict "gene-trait" associations and design breeding experiments [1][2]. Group 2: Advancements in Breeding Precision - The AI tool allows breeding researchers to combine superior alleles more accurately, addressing both traditional traits like yield and disease resistance, as well as new demands such as nutritional enhancement and flavor improvement [2]. - The "Fengdeng·Gene Scientist" simulates expert reasoning processes, automating the entire research workflow from hypothesis generation to result analysis, thereby enhancing research efficiency [2]. - The project has already identified new gene functions in rice and maize, with predictions aligning closely with field trial results, indicating a high level of accuracy in the AI's capabilities [2]. Group 3: Future Developments - The research team plans to continuously integrate more crop data, environmental data, and breeding knowledge into the system, evolving it into a comprehensive intelligent breeding platform that covers all species and processes [2].