The Shanghai Academy of AI for Science (SAIS) released the "Top 10 Frontiers in AI for Science" together with partners at the 2024 AI for Science Innovation Forum held in Shanghai on Monday, underscoring a new era of scientific discovery powered by artificial intelligence.

The announcement made with partners, including Fudan University, Beijing-based scientific research institute Swarma Research and Alibaba Cloud, came as AI-driven research has taken center stage, highlighted by Nobel Prizes in Physics and Chemistry awarded for AI applications in scientific studies and the inspiration of science for AI earlier this year.

The frontiers include AI-powered scientific models, which means creating advanced AI models capable of tackling complex scientific problems, such as protein folding and climate modeling; AI-inspired scientific insights, which means developing AI algorithms inspired by biological and physical principles; and AI for scientific infrastructure, which means building AI-powered tools to manage and analyze vast amounts of scientific data.

The fusion of AI and science is akin to a double helix, driving innovation in both fields, enabling people to envision an AI-powered future where machines understand the world and contribute to its understanding, according to SAIS.

The academy said the release of the 10 frontiers is aimed at promoting and supporting more scientists in the field of AI and basic research to deeply integrate and cooperate seamlessly, jointly exploring the new future of scientific intelligence, and creating an "AI Einstein" that can independently discover the unknown laws of the complex world.

The double helix engine of AI and science that promote mutually is leading people into a new era of scientific discoveries, according to SAIS.

It also pointed out that China's advantages lie in basic scientific research currently, as the country has been a leader in the number of papers published in this respect over the past few years.

The next step for China is to allow its scientists in different areas of science and those in AI to better integrate and empower one another, according to the academy.