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被英伟达点名的杭州团队,补上了AI for Science的「最后一公里」

Industry & News Bioinformatics AI

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Merged summary

TL;DR - Hangzhou-based protein design company Lévin released Lévin Harness, an agentic workspace that connects scientific models, analysis tools, compute, data, and reusable workflows. It aims to close the AI-for-science loop from research planning and protein design through result analysis and experimental feedback.

  • General-purpose LLMs plan tasks and interpret natural-language requests, while specialized tools handle protein structure prediction, sequence design, and candidate evaluation.
  • A plugin system standardizes model installation, inputs, outputs, and execution, while supporting local workstations and remote GPU servers.
  • Integrated 3D molecular visualization gives the agent structural context, including selected residues and spatial regions referenced during conversation.
  • Workflows preserve tools, parameters, decision steps, and experimental feedback for iterative reuse; project data, conversations, settings, and API keys remain on the user’s machine.

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被英伟达点名的杭州团队,补上了AI for Science的「最后一公里」

量子位 杰西卡 2026-09-16
Public signals N/A
Providers: Hugging Face · N/A OpenAlex · N/A Publisher · N/A Semantic Scholar · N/A X · N/A Fetched 2026-09-26 14:15:44.873521 UTC

TL;DR - Hangzhou-based protein design company Lévin released Lévin Harness, an agentic workspace that connects scientific models, analysis tools, compute, data, and reusable workflows. It aims to close the AI-for-science loop from research planning and protein design through result analysis and experimental feedback.

  • General-purpose LLMs plan tasks and interpret natural-language requests, while specialized tools handle protein structure prediction, sequence design, and candidate evaluation.
  • A plugin system standardizes model installation, inputs, outputs, and execution, while supporting local workstations and remote GPU servers.
  • Integrated 3D molecular visualization gives the agent structural context, including selected residues and spatial regions referenced during conversation.
  • Workflows preserve tools, parameters, decision steps, and experimental feedback for iterative reuse; project data, conversations, settings, and API keys remain on the user’s machine.
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