yuguo_on_str

phd candidate @hkust-gz
behavioral strategy

[Fei-Fei Li @drfeifei]

https://t.co/Kt50ttQRMJ

[Ada Fang @AdaFang_]

AI Scientists are starting to actually do science. Not just answer questions. Not just run workflows.

Introducing AutoScientists: a decentralized team of AI agents that can generate hypotheses, design experiments, write code, test ideas, analyze failures, and revise strategy as evidence accumulates.

Because real research is not a to do list of tasks.

It is a living search process. Leads emerge, failures matter, teams form around what works, and priorities shift when evidence changes. Much like how a lab of scientists would work on cutting edge research together.

Across GPT training optimization, biomedical ML, and protein fitness prediction, this decentralized structure consistently does better research.

Learn more 👇

@GaoShanghua @marinkazitnik @KempnerInst @HarvardDBMI @Harvard

[Anton Korinek @akorinek]

1/🆕 New NBER paper: 𝗪𝗵𝗲𝗻 𝗗𝗼𝗲𝘀 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗻𝗴 𝗔𝗜 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗣𝗿𝗼𝗱𝘂𝗰𝗲 𝗘𝘅𝗽𝗹𝗼𝘀𝗶𝘃𝗲 𝗚𝗿𝗼𝘄𝘁𝗵?
Under empirically grounded calibrations, a singularity could arrive within just a few years of automating AI research. 🧵
📄 https://t.co/W7ca6Tml4N

[Michela Tincani @MichelaTincani]

My paper on peer effects has been accepted at the JPE @JPolEcon.

I formulate and empirically test a theory of why students influence each other's learning in school: by competing with each other.

I thank the editor, referees, and data editor.

Paper: https://t.co/7TwMwzdtZc

[John B. Holbein @JohnHolbein1]

heterogeneous treatment effects in diff-in-diffs: much ado about nothing?

[CuiMao @CuiMao]

怕输才会紧张，想赢只会兴奋

[soothsayer @iamasoothsayer]

2023: Corona ended
2026: Hantavirus

[Princeton University @Princeton]

Congratulations to Yiyun Li, Robert F. Goheen Professor in the Humanities and Professor of Creative Writing at @PrincetonArts, who has won the #Pulitzer Prize for Memoir or Autobiography with "Things in Nature Merely Grow"! 👏

[Ben Golub @ben_golub]

excited to present this @USC_Econ today!

(a tweet thread/substack version coming soon)

[Jeffrey Wooldridge @jmwooldridge]

The Stata command lwdid is now available on SSC -- it implements Lee and Wooldridge (2025) rolling DiD estimators. The methods are described here: https://t.co/ubKnsajjmT

We provide methods similar to, and motivated by, Callaway and Sant'Anna (2021, Journal of Econometrics).

[Michela Tincani @MichelaTincani]

Easy-to-follow introduction to agentic AI for economists.

[Anjali Adukia @aadukia]

Submit your work using AI in the social sciences to the annual AI in Social Science conference at the University of Chicago! Submissions due May 1!

The conference will be held October 8-9 in Chicago, IL, USA.

@BeckerFriedman @CAAI_Booth @MiiELab

https://t.co/om2rdoepVR

[Zihan "Zenus" Wang @wzenus]

培养research taste，就是培养自己的品菜能力。

但品菜这件事，比做菜更难教。

做菜可以给你食谱，给你计时器，给你步骤。品菜没有标准答案——你只能说"这道菜好"，说不清楚为什么好。但真正会品的人，一口下去就知道：咸了、火候差了半分钟、葱放早了。

research taste也是这样。你能感觉到一篇paper有问题，但说不出来。你看到一个idea，直觉告诉你这个方向不对，但你说不出理由。这种感觉，就是taste在发育的信号。

品菜能力是怎么来的？
> 吃得足够多。 没吃过一百道菜，不知道什么是"正常水平"。读paper也一样。taste的底层是distribution，读过足够多，才知道什么是平庸，什么是真的有东西。只读自己方向的paper，上来一道川菜以为是黑暗料理。
> 吃过真正好的。 光吃多不够。得吃过几道真正的好菜，才有锚点。去顶会找那几篇让所有人都在讨论的paper，认真读，想清楚它好在哪——不是"结果好"，而是它发现了什么别人没发现的东西。
> 自己做过，才真的会品。 没下过厨的人吃饭，只会说好吃不好吃。下过厨的人吃饭，吃的是决策。这个酱加多了，那一步火太急了。做过research，读paper才能读出作者当时的处境——这里为什么这么选，这里有没有埋坑，这里其实可以更简洁。
> 学会区分：食材的问题，还是厨艺的问题 (Topic不好还是paper execution不好)。 食材差，再好的厨师也难救。食材好，手艺差，暴殄天物。
> 品出"缺了什么"，比品出"哪里不好"更难。 普通的品菜能说出"这道菜太咸"。更高的品菜能力是："这道菜差一点, 如果有点酸就能把咸托出来"。 这就需要我们对"哪里不对"有更精准的理解力, 逼着自己问"然后呢"。

品菜能力最终是一种审美。审美不是天生的，但也很难靠刷题训练出来。它是在大量输入、少量输出、反复对照之后，慢慢沉淀下来的判断力。不需要每道菜都做得好，但得清楚地知道：什么是好菜，好在哪，差在哪，自己现在在哪个段位。
品菜能力，就是让你在厨房里不慌的底气。

[Hanming Fang @HanmingF]

My paper on China’s fertility decline is now forthcoming at JDE:

https://t.co/P3nYEj4i5B

[Cursor @cursor_ai]

You can now run Cursor on any machine and control it from anywhere.

Kick off agents from your phone to run on your devbox.

[あさひな @aaiashn]

Awesome AI for Economists
https://t.co/QoNokk8KeJ

[CuiMao @CuiMao]

你好 @DarioAmodei 这就是你们家的产品。

[yuguo_on_str @melter0k]

this guy just simply want to leave the chaotic earth

[Elon Musk @elonmusk]

NASA Artemis passing close to the Moon

[John A. List @Econ_4_Everyone]

PhD decision season. My inbox is more flooded than ever. Prospective PhD students asking some version of the question: "Should I keep going? Is an Econ PhD still worth it in the age of AI?"

I get it. The uncertainty is real. And, honestly no one knows the answer. My response begins with the caveat that I have no real certainty around my thoughts, I merely have a hunch. And, that intuition comes from combining my experiences in the academy with my recent field work alongside charities, governments, Walmart, and Anthropic itself.

My hunch is that AI will reveal expertise, not replace it, at least for the foreseeable future. Indeed, I wrote about this earlier with my justification.

As such, I do not view a PhD in economics as a credential. It's a forcing function for building that kind of deep, durable expertise. The expertise that AI amplifies rather than erodes.

So my advice? The uncertainty about AI may be the best reason yet to double down and go for an econ PhD. Why? Because the future belongs to people who know things deeply enough that AI becomes a multiplier, not a replacement.

[Kimi.ai @Kimi_Moonshot]

Come introduce yourself to the team, we have your slippers ready.

Reach out at: [email protected]