FutureFinTech lecture: Decoding Evolutionary Art Patterns with vLLMs

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Description

This lecture presents DEAP, an AI-driven framework that analyses how art evolves across cultures by combining visual analysis of artworks with surrounding texts (catalogues, critiques, archives). The framework detects large-scale patterns like secularisation and transnational influence at scale, something traditional art history methods struggle to achieve.

Using multimodal and domain-adapted Large Language Models, DEAP links visual features (composition, colour, form) with contextual language signals (iconography, sentiment, symbolism). The project delivers interactive tools, timelines, similarity maps, and influence networks for scholars, curators, educators, and the public. Intriguingly, the results may also find industry application in FinTech, particularly in automating financial evaluation of private assets.

Join us for expert insights and audience Q&A. This event will be in English.

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