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从DOE转向贝叶斯优化：用AIFD平台快速高效完成工艺开发.
本文将深入剖析为何从DOE转向贝叶斯优化是工艺开发的一次战略性升级，并详细介绍AIFD平台如何通过其独特的工作理念与流程，让这一高效的优化方法触手可及。
快速上手 - 5因子3目标优化实战.
本章的目标是让您在最短的时间内，体验一次从因子定义到获得优化建议的完整流程，从而对AIFactorDesign的核心价值建立一个直观的认识。
A Guide to Smart Experiments: How "Rough Estimates" Can Cut Material Discovery Costs by 68%
How can 'rough estimates' slash nearly 70% off your R&D costs for new materials? This guide reveals the answer. We dive into a recent study from a Nature journal that provides the first "pitfall-avoidance" guide for the powerful Multi-Fidelity Bayesian Optimization (MFBO) technique. With just two simple metrics, you can determine when to safely leverage cheap data to accelerate research and avoid being led astray. Click to learn how AI can save you money with precision and efficiency.
智慧实验新指南：如何用“粗略估计”为新材料发现节省68%的成本？
如何用“粗略估计”为新材料研发节省近七成成本？这篇新指南为你揭晓答案。我们深入解读了发表于《自然》子刊的最新研究，它为强大的多保真贝叶斯优化（MFBO）技术提供了首个“避坑”指南。只需两个简单指标，就能判断何时能安全地利用廉价数据加速研发，避免误入歧途。点击链接，了解如何让AI为你精准、高效地省钱。