SOURCE-LINKED INTELLIGENCE

AutoML Co-Designer: A Collaborative Framework for Accelerated AI Development

CORDIS · observation · Publication date unknown

work for Accelerated AI Development The growth of the AI market depends on our ability to rapidly and efficiently develop robust AI applications, for which AI developers can be supported by Automated Machine Learning (AutoML), e.g., in model selection, neural network design, or hyperparameter settings. However, current AutoML systems are designed as rigid 'black boxes' and thus create a critical bottleneck. They sideline expert developers, preventing the integration of crucial domain knowledge. This inflexibility slows down development cycles, hinders innovation, and limits the creation of sophisticated, market-ready AI solutions for complex, high-value problems. This project, AutoML Co-Designer, will deliver the proof of concept for a collaborative development paradigm that directly addresses this efficiency gap. Our objective is to validate a framework that transforms AutoML from a simple automation tool into a powerful interactive system between AutoML and AI developers. We will engineer and validate a prototype platform with novel interactive interfaces. This platform will serv

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recordType

award

status

SIGNED

region

EU

value

150000

unit

EUR