AWS custom AI silicon helped Metagenomi cut AI bill 56%

"These therapies rely on identifying enzymes - essentially biological catalysts that facilitate chemical reactions - that can bind to the RNA sequences that guide them to their destination, cut the target DNA in the right spot, and - critically - fit in the delivery mechanism of choice. To find these enzymes, the startup is using a class of generative AI known as protein language models (PLMs), like Progen2, to rapidly generate millions of potential candidates."

""It's about finding that one thing in a million. So if you've got access to twice as many, you're doubling your chances of potentially getting a product at the end," Brown said. Developed by researchers at Salesforce, Johns Hopkins, and Columbia Universities in 2022, Progen2 is an auto-regressive transformer model not unlike GPT-2. But rather than spitting out strings of text, it synthesizes novel protein sequences."

Metagenomi, founded in 2018, uses CRISPR to edit gene sequences and develop therapies that address disease causes at the genetic level. The discovery process focuses on identifying enzymes that bind RNA guides, cut target DNA precisely, and fit delivery mechanisms. The company employs protein language models such as Progen2 to generate millions of candidate protein sequences and increase the odds of finding effective enzymes. For trials, Metagenomi compared AWS Inferentia 2 accelerators with Nvidia L40S GPUs and reported that using Inferentia 2 cut costs by 56% while scaling model inference for rapid candidate generation.

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