Sharing Evo 2, a new foundation model for biomolecular sciences, now available on NVIDIA BioNeMo. This is a collaboration between the Arc Institute, Stanford, UC Berkeley, UCSF, and NVIDIA. It's significant because it's trained on a massive dataset – nearly 9 trillion nucleotides of DNA, RNA, and protein sequences from across the tree of life.
Key aspects:
🧬 Genomic Scale: Trained on an enormous dataset covering diverse species. 🔬 Multimodal: Understands DNA, RNA, and protein sequences. 🧠 Long Context: Can process sequences up to 1 million nucleotides at once. 🚀 Powerful Architecture: Uses a "StripedHyena 2" architecture for efficiency. ✅ Open Components: Key parts, including fine-tuning, are available via the open-source NVIDIA BioNeMo Framework. 🔓Available as NVIDIA NIM microservice.
They've already shown it can predict the effects of gene mutations with high accuracy, and even design functional CRISPR-Cas systems. It's a powerful tool for anyone working with biological sequence data.
So, while AlphaFold primarily predicted existing structures, Evo 2 opens the door to designing entirely new biological sequences for things like drug discovery, agriculture, and materials science. What new possibilities does this unlock?
This is massive. A model that not only interprets but designs new biological sequences could push biotech into entirely new territory. The ability to process million-nucleotide sequences means we’re looking at real potential for breakthroughs in genetic engineering, synthetic biology, and even personalized medicine. Excited to see how researchers put Evo 2 to work!
Congrats on the launch!
Best wishes and sending lots of wins to the team behind it :)
Congratulations on the launch of Evo 2! This is a significant advancement in genomic research. How does the model handle the complexities of genomic data variability across different species to ensure accurate and reliable insights?
Congratulations on the launch of Evo 2! This groundbreaking model has the potential to revolutionize multiple fields, from drug discovery to agricultural innovation. The ability to design novel biological sequences is a game-changer for the entire scientific community. I'm excited to see the amazing impact it will have in research and industry. 🚀
Congratulations on the release of Evo 2! This model represents a significant advancement in genomic understanding. How do you ensure the accuracy and reliability of insights across the diverse species covered by the model?
Hi everyone!
Sharing Evo 2, a new foundation model for biomolecular sciences, now available on NVIDIA BioNeMo. This is a collaboration between the Arc Institute, Stanford, UC Berkeley, UCSF, and NVIDIA. It's significant because it's trained on a massive dataset – nearly 9 trillion nucleotides of DNA, RNA, and protein sequences from across the tree of life.
Key aspects:
🧬 Genomic Scale: Trained on an enormous dataset covering diverse species.
🔬 Multimodal: Understands DNA, RNA, and protein sequences.
🧠 Long Context: Can process sequences up to 1 million nucleotides at once.
🚀 Powerful Architecture: Uses a "StripedHyena 2" architecture for efficiency.
✅ Open Components: Key parts, including fine-tuning, are available via the open-source NVIDIA BioNeMo Framework.
🔓Available as NVIDIA NIM microservice.
They've already shown it can predict the effects of gene mutations with high accuracy, and even design functional CRISPR-Cas systems. It's a powerful tool for anyone working with biological sequence data.
So, while AlphaFold primarily predicted existing structures, Evo 2 opens the door to designing entirely new biological sequences for things like drug discovery, agriculture, and materials science. What new possibilities does this unlock?
@zaczuo The future of drug discovery, genetics, and synthetic biology just got a powerful upgrade! 🚀🔬
@zaczuo Awesome blend of Biotech & AI.
Awesome project Zac!
Shram
This is massive. A model that not only interprets but designs new biological sequences could push biotech into entirely new territory. The ability to process million-nucleotide sequences means we’re looking at real potential for breakthroughs in genetic engineering, synthetic biology, and even personalized medicine. Excited to see how researchers put Evo 2 to work!
Congrats on the launch!
Best wishes and sending lots of wins to the team behind it :)
Высокий уровень!
Congratulations on the launch of Evo 2! This is a significant advancement in genomic research. How does the model handle the complexities of genomic data variability across different species to ensure accurate and reliable insights?
Congratulations on the launch of Evo 2! This groundbreaking model has the potential to revolutionize multiple fields, from drug discovery to agricultural innovation. The ability to design novel biological sequences is a game-changer for the entire scientific community. I'm excited to see the amazing impact it will have in research and industry. 🚀
It's weird but good.
Congratulations on the release of Evo 2! This model represents a significant advancement in genomic understanding. How do you ensure the accuracy and reliability of insights across the diverse species covered by the model?