'Every living thing on Earth runs on the same programming language': How AI foundation models trained on DNA could transform plant biology
Our exclusive interview with Living Models CEO and co-founder Cyril Véran
· TechRadarFeatures By Desire Athow Contributions from Wayne Williams published 29 March 2026
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Artificial intelligence has already having a big impact on fields like language processing and computer vision, but biology is emerging as one of the next major frontiers.
Instead of training models on text or images, researchers are now turning to DNA, RNA, and other biological data, treating genetic sequences as information systems that can be analyzed at scale.
That move comes at a moment when genomic data is growing faster than many traditional tools can handle. Sequencing technology has become cheaper and more widespread over the past two decades, producing vast collections of biological data that researchers can read but still struggle to interpret in meaningful ways.
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The challenge is no longer gathering genetic information, but understanding how different sequences interact and influence real-world outcomes.
Enter Living Models
Living Models is part of a growing group of companies attempting to tackle that gap using transformer-based architectures, the same underlying approach that powered the recent wave of large language models.
Instead of predicting the next word in a sentence, these systems analyze patterns across biological sequences, aiming to uncover structural relationships that traditional statistical tools often miss.
The company’s first model family focuses on plant biology, an area where genetic data is widely available and where faster insight could directly affect crop development and climate resilience.
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