Chinese artificial intelligence researchers have released an open-source framework and a real-world scenario competition platform that significantly improves AI industrial application.

As AI computing power grows stronger and large language models become increasingly sophisticated, Chinese researchers have been focused on how best to apply the fast-growing technology to real-world scenarios.

To this end, a research initiative at the artificial intelligence innovation center at the Yangtze Delta Region Institute of Tsinghua University standardized human-machine interactions, task-set mechanisms and human feedback systems, resulting in enhanced industrial application efficiency and greater enterprise deployment.

The team leader said that the global AI sector currently faces a structural contradiction: the exponential growth of model and tool capabilities versus the linear climb in industrial adoption rates. The core contradiction in AI development has shifted from "enhancing model intelligence" to "bridging the deployment gap".

To address the gap between AI capabilities and real-world deployment, the team released the Real World AI open-source framework, expanding the scope of open-source efforts from code and tools to encompass role definitions, workflow design, human-machine interaction and human-human collaboration as an integrated practice.

The framework reconstructs the interaction between AI and humans in real-world tasks through three core elements: restoring real-world task sets, capturing authentic human feedback from real interactions and standardizing human-machine interaction protocols.