生成型人工智能辅助蛋白质设计必须考虑重新利用潜在的潜力
Sean Ekins1, Maximilian Brackmann2, Cédric Invernizzi2
1Collaborations Pharmaceuticals, Inc., Raleigh, North Carolina, USA.
GEN biotechnology
|November 6, 2023
概括
生成型人工智能 (AI) 为药物发现和蛋白质设计提供了新的可能性. 生物技术界必须讨论这些强大的AI工具的安全风险和访问控制.
科学领域:
- 生物技术是生物技术.
- 计算化学计算化学
- 人工智能的人工智能
背景情况:
- 生成型人工智能 (AI) 软件在科学研究中越来越多地被使用.
- 人工智能工具显示出化学和蛋白质设计应用的巨大潜力.
- 这些人工智能技术的重新利用潜力需要进行彻底的评估.
研究的目的:
- 突出生成性AI在化学和蛋白质设计中的重用潜力.
- 倡导社区广泛讨论人工智能在生物技术中的安全影响.
- 建议考虑在科学应用中对AI软件的访问限制.
主要方法:
- 关于当前分子设计中的AI应用的文献综述.
- 分析与生成AI相关的潜在安全漏洞.
- 关于在生物技术中负责任地部署人工智能的框架建议.
主要成果:
- 生成性AI为加速化学和蛋白质设计提供了新的途径.
- 与人工智能工具的广泛使用相关的重大安全考虑和风险.
- 滥用的可能性需要采取积极的安全措施和访问协议.
结论:
- 生物技术界必须就生成性AI的安全性展开公开对话.
- 实施访问限制和使用指南对于降低风险至关重要.
- 负责任的开发和部署是利用人工智能的好处的关键,同时确保安全.
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