Google AI Decodes Genomes of 17 Endangered Species: The Backup of Life Has Begun

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UPDATE (2026-02-03): Expanded to 17 species, added specific species names and EBP 4,386 species data

Google AI Decodes Genomes of 17 Endangered Species: Backup of Life Begins

  • Google uses AI to decode the genomes of 17 endangered species
  • The key is a set of 3: DeepVariant, DeepConsensus, and DeepPolisher
  • Earth BioGenome Project, 4,386 species secured

What happened?

Google used AI to decode the genomes of 17 endangered species. 4 species were added from the initial 13. [Google Blog] Simply put, it’s backing up genes before extinction.

What specific species are they? They include the cotton-top tamarin living in the forests of northwestern Colombia, the golden mantella frog of Madagascar, and the African penguin off the coast of South Africa-Namibia. [Google Blog]

Google.org is expanding the project by supporting the AI for Science Fund at Rockefeller University. It collaborates with the Vertebrate Genomes Project and the Earth BioGenome Project (EBP). [New Atlas]

Why is it important?

Genomic data is needed to develop conservation strategies. New Zealand’s kakapo (a nocturnal flightless parrot) is recovering from near extinction through genome analysis. [Google Blog]

The key is speed and accuracy. DeepVariant reduced genetic variation detection errors by 22-52%. [DeepVariant] DeepConsensus increased high-quality sequencing throughput by 250%. [GitHub] DeepPolisher further reduced genome assembly errors by 50%. [Blockchain News]

Personally, I think this is the real value of Google AI, more than LLM.

What will happen in the future?

EBP has secured approximately 4,386 genomes, with an initial target of 10,000 species by 2026. [EBP] The ultimate goal is to decode all 1.8 million species. The cost is estimated at approximately $5 billion. [Wikipedia]

Frequently Asked Questions (FAQ)

Q: Can genome decoding prevent extinction?

A: It doesn’t directly prevent it. However, genetic diversity analysis can be used to design breeding programs. Like the kakapo, it becomes a key tool for identifying the risk of inbreeding and maintaining a healthy population.

Q: What is the difference between DeepVariant, DeepConsensus, and DeepPolisher?

A: DeepVariant is a CNN-based tool for finding genetic variations in sequencing data. DeepConsensus is a transformer model that corrects errors in PacBio long-read data. DeepPolisher further catches errors in the genome assembly stage. Using them together increases both accuracy and throughput.

Q: Can the general public contribute?

A: All three tools are open source. Researchers can use it directly from GitHub. The general public can contribute by participating in the EBP citizen science program or by sponsoring conservation organizations.

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