---
id: 20260325-T0-02
title: "材料发现为何没有AlphaFold？十年AI科研经验谈"
title_en: "Why No 'AlphaFold for Materials'? A Decade of AI Science Lessons"
url: https://ai.daily.yangsir.net/daily/20260325-T0-02
issue_date: 2026-03-25
publish_date: 2026-03-24T16:53:15.000Z
category: insight
source_name: "Latent Space"
source_url: https://www.latent.space/p/materials
---

# 材料发现为何没有AlphaFold？十年AI科研经验谈

麻省理工学院教授Heather Kulik分享材料科学AI应用的十年经验。她指出，虽然AlphaFold在蛋白质结构预测取得突破，但材料发现仍面临数据稀疏、实验验证周期长等独特挑战。Kulik提出需要建立材料科学专属的AI方法论，并强调跨学科合作的重要性。访谈中还探讨了近期材料AI研究的进展与未来方向。

## English Version

**Why No 'AlphaFold for Materials'? A Decade of AI Science Lessons**

MIT's Heather Kulik shares a decade of experience in AI for materials science. She notes that while AlphaFold revolutionized protein folding, materials discovery faces unique challenges like sparse data and long experimental cycles. Kulik advocates for materials-specific AI methodologies and emphasizes cross-disciplinary collaboration. The discussion covers recent advances and future directions.

---

**来源**：[Latent Space](https://www.latent.space/p/materials)

**详情页**：https://ai.daily.yangsir.net/daily/20260325-T0-02

---

*智语观潮 · Daily — https://ai.daily.yangsir.net/llms.txt*