New AI approaches to help understand complex biological data
Researchers at Cardiff University have introduced a new AI architecture called Vector Bundle Attention (VBA) to better analyze complex biological data. This method improves how AI interprets geometric relationships within tissues and cells, which is crucial for medical research.
Why it matters
Advancements in geometric AI could significantly accelerate drug discovery and the understanding of disease progression at a cellular level.
edited by Lisa Lock , reviewed by Andrew Zinin
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Add as preferred source Credit: Pixabay/CC0 Public Domain Researchers at Cardiff University have presented two studies at the 2026 International Conference on Machine Learning ( ICML 2026 ) that address fundamental challenges in modern AI: understanding the complex geometry and relationships within data and recognizing patterns that occur across very different scales.
Dr. You Zhou, senior lecturer at Cardiff University's School of Medicine and senior author of the studies, said, "Biological research generates enormous amounts of complex data, but much of today's AI still struggles to understand the way biological systems are naturally organized. Cells interact within tissues, and important patterns can appear at many different scales.
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