Evo 2Arc Institute
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Odyssey-3Odyssey
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About
Evo 2 is a genomic foundation model capable of generalist prediction and design tasks across DNA, RNA, and proteins. It utilizes a frontier deep learning architecture to model biological sequences at single-nucleotide resolution, achieving near-linear scaling of compute and memory relative to context length. Trained with 40 billion parameters and a 1 megabase context length, Evo 2 processes over 9 trillion nucleotides from diverse eukaryotic and prokaryotic genomes. This extensive training enables Evo 2 to perform zero-shot function prediction across multiple biological modalities, including DNA, RNA, and proteins, and to generate novel sequences with plausible genomic architecture. The model's capabilities have been demonstrated in tasks such as designing functional CRISPR systems and predicting disease-causing mutations in human genes. Evo 2 is publicly accessible via Arc's GitHub repository and is integrated into the NVIDIA BioNeMo framework.
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About
Odyssey-3 is a foundation world model and learned dynamical system that predicts how objects move and interact through space and how situations evolve over time. Implemented as an autoregressive diffusion transformer, it learns representations of physics, dynamics, and cause-and-effect from a broad dataset of visual observations and uses that knowledge to simulate environments and train policies for physical systems. Odyssey-3 can generate embodied environments from a prompt and predict in real time how they change as a person or agent acts or introduces events, with first-person and third-person navigation and independent camera movement. Its learned world knowledge can be adapted to different systems by training an action decoder or policy on paired observations and actions. With relatively small amounts of task-specific data, Odyssey-3 has been used to control robot arms, power humanoids, drive vehicles, and generate synchronized multi-sensor observations. It can also provide intera
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Platforms Supported
Windows
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Mac
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Linux
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Cloud
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On-Premises
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Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
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Android
Not Supported
Chromebook
Not Supported
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Audience
Computational biologists and genetic engineers in need of a tool to model and design biological sequences across multiple modalities, enhancing research in genomics and synthetic biology
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Audience
AI developers, teams, and researchers seeking to simulate dynamic environments, train agents, and adapt learned world knowledge to robots, vehicles, drones, and physical systems
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Support
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24/7 Live Support
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Support
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API
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Pricing
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Reviews/
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Training
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Company InformationArc Institute
United States
arcinstitute.org/tools/evo
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Company InformationOdyssey
Founded: 2023
United States
odyssey.systems/meet-odyssey-3
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Integrations
Evo Designer
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GitHub
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Hugging Face
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NVIDIA BioNeMo
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Integrations
Evo Designer
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GitHub
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Hugging Face
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NVIDIA BioNeMo
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