Forget "eye of newt and toe of frog/wool of bat and tongue of dog." People in the 16th century were more akin to DIY scientists than Macbeth’s three witches when it came to concocting home remedies for everything from hair loss and toothache, to kidney stones and fungal infections. Medical manuals targeted to the layperson were hugely popular at the time, according to Stefan Hanss, an early modern historian at the University of Manchester in the UK. "Reader-practitioners" would tinker with the various recipes, tweaking them as needed and making personalized notes in the margins. And they left telltale protein traces behind as they did so.
├── /api/smiles-to-xyz SMILES → 3D XYZ (RDKit multi-conformer + MMFF94)
。PDF资料是该领域的重要参考
在大数据领域，数据血缘早已成为治理与溯源的核心能力。然而，在 AI 工程化实践中，从原始数据到最终推理结果的全链路血缘追踪长期处于空白状态——模型训练依赖哪些数据？某次推理异常是否源于早期数据污染？这些问题缺乏系统性答案。DataWorks 率先推出 AI 全链路血缘追踪能力，填补行业空白。该能力覆盖完整 AI 生命周期：从数据集导入、通过 Spark 或 Ray 进行清洗与特征工程，到预训练、微调（SFT）、模型注册，再到部署与在线推理服务，每一步的数据流动与任务依赖均被自动捕获并可视化。基于统一元数据服务和调度引擎，系统可精准关联数据版本、代码任务、模型快照与服务接口，实现“一图看尽 AI 血缘”。这不仅提升了模型可解释性与调试效率，更满足金融、自动驾驶等高合规场景对 AI 审计与责任追溯的严苛要求，真正让 AI 开发变得透明、可信、可管。
Alignment Imprint Detection