🎈 The Story: A Festive Experiment
A Human Question 一个充满人情味的问题
What is the flavour of a pink sphere? The author begins with this seemingly absurd question, pointing out that our brains constantly merge senses. This isn't just a quirky thought; marketers use these associations to design packaging, like making bitter chocolate taste sweeter by wrapping it in pink. 一个粉红色的球体是什么味道？作者以这个看似荒谬的问题开篇，指出我们的大脑在不断地融合各种感官。这并非只是一个古怪的想法；营销人员正是利用这些联想来设计包装，比如用粉色包装纸包裹苦巧克力，让它尝起来更甜。
Posing the Question to AI 向人工智能提问
Inspired by how humans connect senses, researchers and the author decided to test if AI does the same. They asked ChatGPT questions like "which colour best goes well with sweet tastes?" The AI's answers surprisingly mirrored human consensus. 受到人类如何连接感官的启发，研究人员和作者决定测试人工智能是否也会这样做。他们向 ChatGPT 提出了诸如“哪种颜色与甜味最搭配？”之类的问题。出人意料的是，人工智能的回答与人类的共识如出一辙。
Christmas Accompaniments 圣诞节的完美搭配
Putting the theory to a festive test, the author asked ChatGPT for music recommendations to pair with mulled wine. The AI didn't just pick random Christmas songs. It analyzed the "flavor profile" of the wine and suggested music to match. 为了对这一理论进行节日测试，作者向 ChatGPT 寻求与热红酒搭配的音乐建议。人工智能并不仅仅是随机挑选圣诞歌曲，而是分析了酒的“风味特征”，并推荐了与之匹配的音乐。
"The complex flavour profile of mulled wine... calls for music that is equally layered, warm, and evocative. A perfect accompaniment could be Carol of the Bells..." “热红酒复杂的风味特征……需要同样层次丰富、温暖且富有感染力的音乐。一个完美的搭配可以是《钟声颂》……”
When asked for alternatives, it suggested jazz and pop songs, like Ella Fitzgerald's "Have Yourself a Merry Little Christmas," describing its "sultry, smooth tones" as echoing the "comforting and layered flavours of the mulled wine." 当被问及其他选择时，它推荐了爵士和流行歌曲，如艾拉·费兹杰拉的《祝你有个快乐的小圣诞》，并将其“ sultry, smooth tones”（性感流畅的音色）描述为与“热红酒 comforting and layered flavours”（慰藉人心且层次丰富的风味）相呼应。
🔮 Knowledge Extension: The AI Party Planner 🔮 知识拓展：人工智能派对策划师
Think of the AI like a chef who is also a DJ. It doesn't just know recipes and song lists. It "tastes" the ingredients of an experience (like the cinnamon and clove in wine) and finds music with the same "flavor notes" (warmth, complexity, tradition). It's matching the feeling, not just the category. 把人工智能想象成一位既是厨师又是DJ的大师。它不只懂食谱和歌单，更能“品尝”体验中的各种元素（比如酒里的肉桂和丁香），然后找到具有相同“风味音符”（温暖、复杂、传统感）的音乐。它匹配的是感觉，而不仅仅是类别。
Hover over the wine glass to see its flavor notes spread out and influence the atmosphere! 将鼠标悬停在酒杯上，看看它的风味音符如何散开并影响氛围！
🔬 The Science: Cross-Modal Correspondences
"Eating with the Eyes" “用眼睛吃饭”
Scientists call the linking of different senses "cross-modal correspondences." Our brain doesn't keep senses separate. Information from our eyes (sensory modality: vision) directly influences our tongue (sensory modality: taste). This phenomenon is a fundamental part of how we perceive the world. 科学家将不同感官之间的联系称为“跨感官对应”。我们的大脑并不会将各种感官完全分开。来自眼睛的信息（感官模式：视觉）会直接影响我们的舌头（感官模式：味觉）。这种现象是我们感知世界方式的一个基本组成部分。
Learned Associations: Colors and Shapes 后天习得的联想：颜色与形状
Research shows strong, cross-cultural patterns: 研究显示了强烈的、跨文化的模式：
- **Color:** Red/Pink → Sweet. Yellow/Green → Sour. Black/Brown → Bitter.**颜色：** 红色/粉色 → 甜。黄色/绿色 → 酸。黑色/棕色 → 苦。
- **Shape:** Round shapes → Sweet. Spiky/Angular shapes → Sour or Bitter.**形状：** 圆形 → 甜。尖锐/有棱角的形状 → 酸或苦。
The leading theory, by Prof. Charles Spence, is that we learn these from our environment. Ripe fruits are often red and sweet, while unripe ones are green and sour. We internalize these natural statistics. Similarly, we might associate sharp shapes with danger (and poison, which is often bitter) and round shapes with safety and pleasure. 牛津大学的查尔斯·斯宾塞教授提出的主流理论认为，我们是从环境中学习到这些联想的。成熟的果实通常是红色且甜的，而未成熟的则是绿色且酸的。我们将这些自然界的统计规律内化了。同样，我们可能将尖锐的形状与危险（以及通常是苦味的毒药）联系起来，而将圆形与安全和愉悦联系起来。
Associative AI: A Mirror to Our Mind 联想型AI：我们心智的一面镜子
When researchers asked AI models like ChatGPT and Gemini about these pairings, they gave answers that strongly matched human results. This isn't because the AI "feels" sweetness. It's because the AI has been trained on vast amounts of human-generated text and images where these associations are implicitly embedded. 当研究人员向 ChatGPT 和 Gemini 等人工智能模型询问这些配对时，它们给出的答案与人类的结果高度吻合。这并非因为人工智能能“感觉”到甜味，而是因为它在大量的人类生成的文本和图像数据上进行了训练，而这些数据中隐含着这些联想。
"Given that we tested the large language models on what is already known... maybe it's just feeding back what it has read." - Prof. Charles Spence “考虑到我们是在已知的基础上测试这些大型语言模型的……也许它只是在反馈它所读到的内容。” —— 查尔斯·斯宾塞教授
The AI acts as a giant mirror, reflecting the collective, often unconscious, biases of human culture. This makes it a powerful tool for discovering and testing these psychological links. 人工智能就像一面巨大的镜子，反映了人类文化中集体的、常常是无意识的偏见。这使其成为发现和测试这些心理联系的强大工具。
💡 Knowledge Extension: The Brain's Flavor Dictionary 💡 知识拓展：大脑的风味词典
Imagine your brain has a special dictionary that translates between senses. It learns that the visual "word" for a strawberry (red, round) means the same thing as the taste "word" for sweet. This dictionary isn't pre-installed; you write it yourself every time you eat, see, and experience the world. 想象一下你的大脑里有一本特殊的词典，可以在不同感官之间进行翻译。它通过学习得知，草莓的视觉“词汇”（红色、圆形）与甜味的味觉“词汇”意思相同。这本词典并非预装的，而是你在每一次饮食、观察和体验世界时亲手编写的。
Visual Word + Shape Word → Taste Word视觉词汇 + 形状词汇 → 味觉词汇
🍓 + 🍬 → 😊 (Sweet / 甜)
🍋 + ⚡️ → 😖 (Sour / 酸)
☕️ + 뾰 → 🤢 (Bitter / 苦)