顾全全(Quanquan Gu)于 2026 年 6 月 2 日发文宣布离开字节跳动 Seed,结束三年任职。过去三年他主导 AI 驱动的药物发现方向,团队产出生物分子结构预测模型 SeedFold、蛋白质 binder 设计模型 SeedProteo 和 DPLM 系列蛋白质语言模型。
字节跳动的顾全全的简要履历一览:
从清华大学到 UCLA,再到字节 Seed 的 3 年
今天(2026年6月2日),顾全全教授发文宣布离开字节 Seed。
过去三年,他同时在两个最难的 AI 方向深耕:AI 驱动的药物发现 和 前沿大模型的训练与 scaling。
学术履历
•清华大学自动化系本科、硕士
•2014 年 UIUC 计算机科学博士(导师 Jiawei Han)
•现为 UCLA 计算机科学教授,创办 UCLA AGI Lab
•长期研究方向:机器学习、优化理论、大模型与 AI for Science
字节 Seed 核心贡献
① AI for Drug Discovery(主导,2023–2026)
带领团队构建了多个在行业内达到 SOTA 的模型:
•SeedFold:全球首个在多项 benchmark 上全面超越 AlphaFold 3 的生物分子结构预测模型
•SeedProteo:蛋白质 binder 设计模型,性能超过 AlphaProteo、RFdiffusion、Chai-2 等
•DPLM 系列:蛋白质语言模型
这些工作真正把大模型能力落地到“用 AI 治病”这一真实场景。
② LLM Pretraining & Scaling(2025 年起组建团队)
2025 年初,他组建了 LLM optimization and scaling 团队,专注解决超大模型稳定训练和扩展的核心难题。
团队搭建了高度可扩展的预训练技术栈,直接支撑了 Seed 2.0 及后续多个前沿规模模型的成功训练。
顾全全教授是少数同时在「AI for Science」和「前沿模型工程」两个赛道都做出实质性突破的学者。
Today marks my last day at ByteDance Seed. Over the past 3 years, I had the opportunity to work across two of the most exciting frontiers in AI: AI for Drug Discovery and building frontier LLMs. Few opportunities in a career allow one to work simultaneously on curing disease and building frontier intelligence. I was fortunate to do both. Since joining ByteDance, I have led the AI for drug discovery effort. Together with an exceptional team and collaborators, we built SeedFold, the world's first biomolecule structure prediction model to outperform AlphaFold 3 across a broad range of benchmarks and capabilities; SeedProteo, a state-of-the-art protein binder design model surpassing AlphaProteo, RFdiffusion, Chai-2, BinderCraft, and BoltzGen ; and the DPLM series of protein language models, along with several other ambitious AI for Science projects. In early 2025, I took on a new challenge. To tackle one of the hardest problems in modern AI, reliably training and scaling frontier-scale LLMs, I joined the LLM pretraining effort and founded the LLM optimization and scaling team. Together, we built a highly scalable pretraining stack that enabled the successful training of Seed 2.0 and the subsequent frontier-scale models, significantly advancing our ability to train and iterate on frontier AI systems at scale. I'm deeply grateful to my teammates, collaborators, and leadership for an incredibly rewarding journey. The best model is yet to come. Scaling continues!在 X 查看被引用的帖子
来源:@berryxia · x.com