SOURCE-LINKED INTELLIGENCE

Data-efficient model training for sustainable artificial intelligence

CORDIS · observation · Publication date unknown

Data-efficient model training for sustainable artificial intelligence Artificial intelligence (AI) has become integral to modern life, with applications ranging from healthcare, medical diagnostics to cultural heritage preservation. Recent progress in foundation models, notably vision-language models (VLMs) and multimodal large language models, has demonstrated remarkable capabilities across diverse tasks. Yet, their training and deployment demand enormous computational resources, creating significant environmental costs and limiting accessibility. Current research emphasises scaling models and datasets to boost performance, but comparatively little attention is given to the usage efficiency and quality of the underlying data. A key question arises: must we always rely on all available data, or can similar performance be achieved with substantially less data, thereby reducing costs and environmental impact? This proposal, DeTAI, add

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recordType

award

status

SIGNED

region

EU

value

260347.92

unit

EUR