Shanghai AI Lab launches 'Scholar Inkstone' platform, aiming to become a 'revolutionary tool' for AI-driven science

The Shanghai Artificial Intelligence Laboratory (Shanghai AI Lab) has unveiled the 'Scholar Inkstone' (Chinese: 书生·端砚) platform, describing it as a 'revolutionary tool' for AI-powered scientific research. The initiative marks a significant step forward in China's AI for Science efforts.

The platform's core mission is to bring large language model and multi-modal AI capabilities into high-end scientific research scenarios. Coverage areas include foundational large model capabilities, nuclear fusion energy research, quantum computing simulation, and other frontier directions. Scientists can leverage the platform to accelerate simulation experiments and analyze complex scientific data without needing to build and train AI models themselves.

Scholar Inkstone is the latest addition to the InternLM (Shusheng) model ecosystem from Shanghai AI Lab. The lab has previously released the InternLM series of large language models, InternEarth for earth sciences, and other AI infrastructure. With the launch of this scientific platform, the lab is signaling a strategic shift from 'building models' to 'building platforms' — creating a unified AI research toolkit for the scientific community.

From a technical perspective, Scholar Inkstone offers end-to-end capabilities spanning data processing, model training, and scientific reasoning. Researchers interact with underlying AI models through natural language, without needing programming or fine-tuning expertise. This dramatically lowers the barrier to AI adoption in non-computer science disciplines.

The global AI for Science race is intensifying. Google DeepMind's AlphaFold has demonstrated AI's revolutionary potential in protein structure prediction, while Microsoft and Meta are investing heavily in materials science and climate simulation. Shanghai AI Lab's move represents China's accelerated push to catch up in this critical domain.

Notably, Scholar Inkstone's emphasis on nuclear fusion and quantum computing targets two of the most scientifically challenging frontiers. These fields represent the future of energy and computational paradigms, where AI is increasingly seen as a key tool for breaking through computational bottlenecks.

For working scientists, Scholar Inkstone promises to shorten the path from scientific question to AI-powered insight. If effectively deployed, it could foster a new 'AI-scientist' collaboration model. Industry observers will be watching closely for the platform's real-world performance in active research projects.