AI4R&D: AI-Driven R&D New Paradigm

With the rapid development of artificial intelligence technology, it is profoundly influencing and reshaping the paradigms of scientific research and industrial R&D. Universities, research institutions, and enterprises are actively promoting the deep integration of AI with research work, exploring the new field of AI4R&D (AI for Research and Development). Currently, AI4R&D has achieved multiple breakthroughs in scientific research and industrial R&D, demonstrating broad development prospects. It is expected to further bridge the last mile between original innovation and industrial applications, promoting faster conversion of scientific achievements into practical applications.

On July 25, 2024, the report "AI4R&D – AI-Driven R&D New Paradigm" was officially released at the 12th plenary meeting of the China Artificial Intelligence Industry Alliance (AIIA).

The report first introduces the connotation of AI4R&D and the overall development trend. It then elaborates on the industrial development of AI4R&D, pointing out that research computing power, research data, and development toolchains have significantly improved the efficiency of research work, while identifying current challenges and opportunities facing the industry. The report also comprehensively reviews the applications of AI4R&D in scientific research and industrial R&D, highlighting significant achievements in new drug discovery, materials development, and industrial simulation. The report emphasizes the importance of industrial ecosystem construction, particularly in areas such as industrial organizations, community building, and standard systems, while providing an outlook on the future development of AI4R&D.

Key Highlights of the Report:

● Revealing the enormous potential of AI4R&D. The report points out its important role in basic scientific exploration and industrial upgrading and transformation. In scientific exploration, it will show broad application prospects in literature research, experimental guidance, new theory discovery, and scientific computing optimization. In terms of industrial upgrading, it will comprehensively empower fields such as biopharmaceuticals, new materials, industrial simulation, and industrial manufacturing.

● Mapping the AI4R&D ecosystem landscape. The report analyzes the current status and development trends of AI4R&D from multiple dimensions including industrial chain, technology and application, and ecosystem construction, with equal emphasis on scientific research and industrial R&D.

● Looking ahead to the future development of AI4R&D. The report outlines future development directions including technological innovation, interdisciplinary integration, industrial application, and policy support.

Report Table of Contents:

1. Development Trend of AI4R&D

2. AI4R&D Industry Development

2.1 Research Computing Power – Enabling Efficient Operation of Scientific Intelligence

2.2 Research Data – Driving Innovative Discovery in Scientific Intelligence

2.3 Development Toolchain – Full-Link Development Tools for AI4R&D

3. AI4R&D Application Development

3.1 Basic Scientific Research – Conducting Frontier Exploration and Expanding Scientific Boundaries

3.2 Industrial R&D Innovation – Building Core Driving Forces and Accelerating Industrial Upgrade and Transformation

4. AI4R&D Ecosystem Construction

4.1 Industrial Organizations

4.2 Community Building

4.3 Research Competitions

4.4 Conference Exchanges

4.5 Education and Training

4.6 Standards Layout

5. Summary and Outlook