Living Models, a Paris–Berkeley startup, has raised $7 million in seed funding as it emerges from stealth to develop foundation models for biology trained on DNA, RNA, and multi-omics data aimed at improving understanding of biological systems.
To support the next stage of development, the company has also secured access to a computing cluster of 120 NVIDIA B200 GPUs, which it plans to use to train its next generation of biological AI models.
The company develops large-scale transformer models trained on genomic, transcriptomic, and other biological datasets to analyse patterns within living organisms. Operating in Paris and Berkeley, Living Models brings together researchers in artificial intelligence and plant science to apply machine learning to biological research and agricultural innovation.
While artificial intelligence has already transformed sectors such as finance, software development, and content creation, its application in areas such as agriculture and food production remains at an earlier stage.
Living Models is focusing on this area by applying AI techniques to biological data, particularly in plant science, where improving crop resilience and productivity is becoming increasingly important as climate pressures affect global agriculture.
As part of its launch, the company introduced BOTANIC, a family of transformer models designed for plant biology. The models are trained on genomic sequences from multiple plant species and analyse genomic and other biological data to identify genetic markers associated with traits such as climate resilience and disease resistance.
By predicting which genetic variants are worth testing, the technology aims to help seed and agricultural companies accelerate the development of new crop varieties.
OpenAI trains on Reddit and Wikipedia to understand human language. We train on DNA, RNA, and gene expression to understand the language of life itself,
said Cyril Véran, CEO and co-founder of Living Models.
Traditional crop breeding cycles can take many years, partly due to the time required to identify promising genetic traits. By analysing genomic data computationally, Living Models aims to shorten the early stages of this process by helping researchers focus on the most relevant genetic variants before conducting field validation.
In the longer term, Living Models plans to expand its work on foundation models for biological systems beyond plants. The company began with plant biology due to the availability of large genomic datasets, faster validation cycles compared with other life-science fields, and the growing need for technologies that support climate-resilient agriculture.
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