The Largest Digital Zoo: Biology Model Trained on NVIDIA GPUs
Tanya Berger-Wolf’s first computational biology project started as a bet with a colleague: that she could build an AI model capable of identifying individual zebras faster than a zoologist.
She won.
Now, the director of the Translational Data Analytics Institute and a professor at The Ohio State University, Berger-Wolf is taking on the whole animal kingdom with BioCLIP 2, a biology-based foundation model trained on the biggest, most diverse dataset of organisms to date. The model will be showcased at this year’s NeurIPS AI research conference.
BioCLIP 2 goes beyond extracting information from images. It can distinguish species’ traits and determine inter-and intraspecies relationships. For example, the model arranged Darwin’s finches by beak size, without teaching the concept of size, shown in the image below.
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