This year in a series co-produced with GenomeWeb we had an exclusive look into Illumina’s work in genomic AI with Kyle Farh, the VP and Distinguished Scientist leading the Illumina Artificial Intelligence Lab.

"We lack a way of training genomic AI as readily as you would for natural language processing,” says Farh. "There are vast amounts of data, but there are no labels, no supervision. One of the most powerful tools that we’ve found is using clues from natural selection.”

Farh says the company began the AI lab seven years ago when deep learning took off. Two of the team’s AI algorithms, PrimateAI-3D and SpliceAI, published in Cell and Nature Genetics, were among the first examples of deep learning algorithms in genomics to become widely used by clinical labs and researchers in interpreting variants of unknown significance.

What will be the long-term impact of AI on genomics?

Chapters:

0:00 First-of-kind studies to utilize AI to decode variation in humans

3:00 Training genomic AI on natural selection

9:10 What sets Illumina’s algorithms apart?

11:40 Insights of PrimateAI-3D and SpliceAI

21:40 How will AI impact genomics long term?

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