做食品推荐系统或菜谱应用的开发者，可以看看化学模型如何超越食谱模型——它可能改变你设计食材搭配逻辑的方式。
伦敦初创公司 Kaikaku.AI 推出名为 Epicure 的三个 AI 模型，首次明确区分食材搭配是基于食谱还是化学分子。模型基于 414 万条多语言食谱和 FlavorDB 风味数据库训练，不同变体给出不同推荐。纯化学模型在口味和营养价值分类上甚至优于食谱模型，尽管从未直接接触这些信息。这项研究揭示了 AI 在食品科学中的新应用方向。
Ask AI what goes with chicken and the answer depends on whether it learned from recipes or molecules
With "Epicure," London-based startup Kaikaku.AI presents three AI models that are the first to clearly separate whether an ingredient fits a recipe or is chemically related. Trained on 4.14 million recipes in seven languages and the FlavorDB flavor database, each variant returns different recommendations. The purely chemistry-based model even classifies taste and nutritional values better than the recipe-based alternatives, despite never seeing that information directly. The article Ask AI what goes with chicken and the answer depends on whether it learned from recipes or molecules appeared first on The Decoder .