Evo 2 is a state of the art DNA language model for long context modeling and design. Evo 2 models DNA sequences at single-nucleotide resolution at up to 1 million base pair context length using the StripedHyena 2 architecture. Evo 2 was pretrained using Savanna. Evo 2 was trained autoregressively on OpenGenome2, a dataset containing 8.8 ...

2025年2月21日 · 团队称， Evo 2 是迄今为止最大的公开 AI 生物学模型，完整版高达400亿参数，包含12.8万个物种的9.3万亿个核苷酸。 它囊括了生物学的基本语言：DNA、RNA 和蛋白质，能够一次分析长达一百万个核苷酸的序列长度。

Evo 2 is a genomic foundation model capable of generalist prediction and design tasks across DNA, RNA, and proteins. It uses a frontier deep learning architecture to enable modeling of biological sequences at single-nucleotide resolution with near-linear scaling of compute and memory relative to context length.

2025年2月19日 · Evo 2, a powerful new AI model built using NVIDIA DGX Cloud on Amazon Web Services (AWS), provides insights into DNA, RNA and proteins across diverse species. Scientists everywhere can now access Evo 2, a powerful new foundation model that understands the genetic code for all domains of life.

Evo 2 是基因组建模领域这一系列研究的新一代产品，基于 Evo 在扩展数据、增强架构和卓越性能方面取得的成功而构建。 Evo 2 可以深入了解三种基本生物分子 (DNA、RNA 和蛋白质) 以及生命的所有三个领域：真核生物 (Eukarya)、原核生物 (Prokarya) 和古菌 (Archaea)。

Evo 2 是美国弧形研究所、英伟达、斯坦福大学等机构合作推出的DNA语言模型，用于基因组建模和设计，覆盖生命的所有领域。 Evo 2 基于 StripedHyena 2 架构开发，以单核苷酸分辨率处理长达100万个碱基对的上下文长度。

3 天之前 · 如今，Evo迎来了重大升级——Evo 2。 Evo 2基于NVIDIA的DGX Cloud平台构建，并在覆盖生命三域（原核生物、古菌、真核生物）超12.8万个物种基因组上进行 ...

2025年2月19日 · Trained on a dataset that includes all known living species – and a few extinct ones – Evo 2 can predict the form and function of proteins in the DNA of all domains of life and run experiments in a fraction of the time it would take a traditional lab.

2025年2月19日，Arc Institute研究团队发布了Evo的升级版Evo 2，其在数据规模、模型架构、预测能力和生成能力等方面的显著升级，为跨生命域的基因组建模与设计提供了强大的支持。

2025年2月21日 · We introduce Evo 2, a biological foundation model trained on 9.3 trillion DNA base pairs from a highly curated genomic atlas spanning all domains of life. We train Evo 2 with 7B and 40B parameters to have an unprecedented 1 million token context window with single-nucleotide resolution.