Thinking Machines 首席科学家 John Schulman 谈及 2015–2017 年以来 AI 领域的变化： “以前这个领域里的人有点更‘怪’一些。” “现在工程能力变得更重要了……相比之下，纯研究、品味以及探索性研究能力的重要性下降了。” “仅仅通过扩展一些简单想法并把执行做好，就已经有大量‘触手可及的成果’。” “拥有更强软件工程背景的人，现在更具优势。” Thinking Machines chief scientist John Schulman on what’s changed in AI since 2015–2017: “Previously the people were a bit weirder.” “Engineering skill matters more now… as opposed to research, taste and the ability to do exploratory research.” “There’s so much low hanging fruit just from scaling the simple ideas and executing on them well.” “People who have more of a software engineering background have more of an advantage now.”

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2025/12/19 07:05 UTC

观点原文

Thinking Machines 首席科学家 John Schulman 谈及 2015–2017 年以来 AI 领域的变化：

“以前这个领域里的人有点更‘怪’一些。”

“现在工程能力变得更重要了……相比之下，纯研究、品味以及探索性研究能力的重要性下降了。”

“仅仅通过扩展一些简单想法并把执行做好，就已经有大量‘触手可及的成果’。”

“拥有更强软件工程背景的人，现在更具优势。”

Thinking Machines chief scientist John Schulman on what’s changed in AI since 2015–2017:

“Previously the people were a bit weirder.”

“Engineering skill matters more now… as opposed to research, taste and the ability to do exploratory research.”

“There’s so much low hanging fruit just from scaling the simple ideas and executing on them well.”

“People who have more of a software engineering background have more of an advantage now.”

1️⃣ AI 正在从“怪才驱动”转向“工程驱动”

2015–2017 年：以研究员、理论突破为中心，更像学术前沿

现在：核心不再是“想出怪点子”，而是把已知方法做大、做稳、做对

2️⃣ “工程能力更重要”是结构性变化

模型路线已相对清晰

真正拉开差距的是：

3️⃣ “低垂的果实”意味着什么

不需要全新理论

只要：

4️⃣ 软件工程背景开始占上风

会写论文 ≠ 能跑系统

能写系统的人：

AI 正从“天才实验室时代”，进入“工程规模化时代”。