Weinan E: AI for Science's second half is rebuilding the research system
Speaking at PAIR Conference 2026 in Shanghai, Chinese Academy of Sciences academician Weinan E argued that AI for Science has two layers: as research becomes “industrialized,” it needs new infrastructure — compute, models/algorithms/software, databases and knowledge bases, and automated labs (China has pushed this “platform research” approach since 2022) — while the “second half” is change in the research system itself. He said theory and computation matter alongside automated labs and literature mining: DPA-4 now covers organic molecules, catalysis and complex interfaces, but is still two to three orders of magnitude from materials and process design, and a “science foundation model” built by fine-tuning open general models may be a false premise if the underlying base model is weak. He also called for breaking three boundaries: theory/experiment, between disciplines, and research/industry.
A systematic assessment from one of the field's earliest advocates, showing that competition in AI for Science is shifting from single model breakthroughs toward infrastructure, base-model capability and research organization.
PAIR Conference 2026Shanghai Institute of Physical Intelligence and RoboticsWeinan E