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Bringing GPT-Rosalind to academic research labs

Introducing the Rosalind Academic Plan, offering eligible academic labs sponsored access to GPT-Rosalind and tools to advance life sciences research.

OpenAI NewsDonnerstag 21:00 · 15.10.3 Min. Lesezeit

Introducing the Rosalind Academic Plan, offering eligible labs sponsored access to GPT‑Rosalind and tools for life sciences discovery.

Share Supporting the research behind future breakthroughs Supporting the research behind future breakthroughs How academic labs are using GPT-Rosalind What the plan includes Build for life sciences research Apply on behalf of your lab Get started with GPT-Rosalind Responsible access for scientific research Get started Supporting the research behind future breakthroughs How academic labs are using GPT-Rosalind What the plan includes Build for life sciences research Apply on behalf of your lab Get started with GPT-Rosalind Responsible access for scientific research Get started We’re introducing the Rosalind Academic Plan to help more academic scientists access GPT‑Rosalind ⁠, our dedicated life sciences model, which combines frontier reasoning with Rosalind workbench ⁠ (opens in a new window) that enables specialized tool orchestration across medicinal chemistry, genomics, wet-lab assistance, and other scientific applications. Eligible labs can receive up to 30 Business Standard seats at no cost for up to 12 months, with access to GPT‑Rosalind subject to trusted-access approval.

Academic research creates knowledge that entire fields build on. Work that begins with a fundamental question about biology can eventually change how we diagnose disease, develop medicines, or grow food. But those advances depend on scientists having the resources to explore ideas, test them, and share what they learn.

Accelerating scientific discovery is central to OpenAI’s mission of ensuring that artificial general intelligence benefits all of humanity. With this plan, we’re investing in the scientists doing that foundational work—helping more labs combine their expertise and judgment with AI tools built for life sciences research.

Many of the advances we rely on today grew out of years of basic research.

The Human Genome Project helped launch modern genomics, transforming medicine, diagnostics, and biotechnology.

Curiosity-driven work on bacterial immune systems led to CRISPR-Cas9, which revolutionized genome editing and is now advancing research in cancer, inherited disease, agriculture, and biotechnology. Decades of university research on mRNA also laid the groundwork for COVID-19 vaccines and a new generation of vaccines and therapies.

Academic research has always laid the groundwork for advances in medicine and biotechnology. By helping more scientists combine their scientific expertise and judgment with the advanced specialized reasoning of GPT‑Rosalind, we hope to support discoveries whose benefits reach far beyond the lab.

OpenAI is committed to enabling academic researchers to pursue their scientific ambitions. Distinguished academic labs are already exploring how GPT‑Rosalind can support work ranging from protein design to understanding neurodegeneration. These examples show where researchers are applying the model within their scientific workflows.

With the new Rosalind Academic Plan, academic researchers can bring GPT‑Rosalind and Rosalind Workbench to their lab with greater flexibility and harness frontier model intelligence for scientific research.

Up to 30 Business Standard seats at $0 per user per month for up to 12 months.

Access to all commercially available frontier OpenAI models, subject to plan usage limits.

Access to GPT‑Rosalind following trusted-access approval.

Research data shared through the Rosalind Academic Plan is not used to train our models by default.

GPT‑Rosalind is a specialized life sciences model designed to support deeper reasoning on complex biological questions. Through trusted access, approved researchers can use it to investigate sensitive scientific questions within safeguards designed for legitimate research.

Designing candidate drugs, therapeutic proteins, peptides, and enzymes, and optimizing their molecular interactions, selectivity, stability, and suitability for development.

Quelle: OpenAI News (OpenAI News). Original öffnen