Learnware Paradigm

The learnware paradigm shifts the focus in machine learning from training large models from scratch to reusing numerous smaller, pre-trained models for new tasks. Current research centers on developing systems, like learnware docks, that allow for the efficient discovery, specification, and assembly of these pre-trained models, even by users with limited expertise. This approach aims to address challenges like data scarcity, privacy concerns, and the high computational cost of large model training, offering a more accessible and sustainable path to machine learning applications.