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Kai S.'s avatar

It’s interesting that the cross-species UCE model is the most performant. InstaDeep recently published their ChatNT genomic model and showed that training on multiple species genomes simultaneously, and selectively switching between objectives, produced a model that generally outperforms specialized models. Makes me wonder whether providing several “escape hatches” in terms of objectives makes the training process more robust to getting stuck in local minima.

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Temitope Leke's avatar

Hello Abhishaike,

I really enjoyed reading this post. I'm particularly excited about it because I'm preparing for an upcoming STEM outreach program for high school students on the applications of AI in single-cell biology. With your permission, I'd love to incorporate some of the points you discussed in my presentation.

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