Nikhil Garg

Interesting paper AND discussion by Proflic folks in the comments

📣 Postdocs at Yale FDS! 📣 Tremendous freedom to work on data science problems with faculty across campus, multi-year, great salary. Deadline 12/15. Spread the word! Application: academicjobsonline.org/ajo/jobs/31114 More about Yale FDS: fds.yale.edu

Dear Mayor-Elect Mamdani, here are 8 gov tech ideas for your first 100 days. - BetaNYC Dear Mayor-Elect Mamdani, here are 8 gov tech ideas for your first 100 days!

How should Mayor Mamdani make #govtech work for all New Yorkers?

@beta.nyc is presenting 8 actionable #CivicTech ideas for the incoming administration. Also, we have gathered community recommendations at the bottom of our ideas.

Read more on here.

www.beta.nyc/2025/11/18/d...

Had a great time at CODE@MIT this weekend, and wanted to highlight a few (of the many) cool talks!

abstract of the paper "What did Elon change? A comprehensive analysis of Grokipedia" Elon Musk released Grokipedia on 27 October 2025 to provide an alternative to Wikipedia, the crowdsourced online encyclopedia. In this paper, we provide the first comprehensive analysis of Grokipedia and compare it to a dump of Wikipedia, with a focus on article similarity and citation practices. Although Grokipedia articles are much longer than their corresponding English Wikipedia articles, we find that much of Grokipedia's content (including both articles with and without Creative Commons licenses) is highly derivative of Wikipedia. Nevertheless, citation practices between the sites differ greatly, with Grokipedia citing many more sources deemed "generally unreliable" or "blacklisted" by the English Wikipedia community and low quality by external scholars, including dozens of citations to sites like Stormfront and Infowars. We then analyze article subsets: one about elected officials, one about controversial topics, and one random subset for which we derive article quality and topic. We find that the elected official and controversial article subsets showed less similarity between their Wikipedia version and Grokipedia version than other pages. The random subset illustrates that Grokipedia focused rewriting the highest quality articles on Wikipedia, with a bias towards biographies, politics, society, and history. Finally, we publicly release our nearly-full scrape of Grokipedia, as well as embeddings of the entire Grokipedia corpus.

back again to share a new preprint from me and @mantzarlis.com! “What did Elon Change? A comprehensive analysis of Grokipedia” arxiv.org/abs/2511.09685

I had seen many spot analyses of individual grokipedia pages, but I was curious: how was grokipedia made? what did Elon change from wikipedia?

For #30DayMapChallenge day 11, a minimal map from @kennypeng.bsky.social.

Kenny extracts minimal elements from a not-as-minimal-as-it-seems object: the Manhattan street grid. "I show how Manhattan’s numbered grid of streets and avenues is more complicated than you might realize," he says.

It's been an absolute pleasure working with Ellen, Madeleine, and their amazing PhD students for the past year on making optimization more accessible with generative AI!

I am on the job market this year - check out my website (conlaw.github.io) for more details on what I've been up to.

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🚨Out in PNAS🚨
Examining news on 7 platforms:
1)Right-leaning platforms=lower quality news
2)Echo-platforms: Right-leaning news gets more engagement on right-leaning platforms, vice-versa for left-leaning
3)Low-quality news gets more engagement EVERYWHERE - even BlueSky!
www.pnas.org/doi/10.1073/...

These are substantial disagreements, which have been partially hashed out here and here. Nevertheless, we've found that all of us have more in common than you might expect. In this essay, we've come together to discuss the ways in which we agree with each other on how AI progress is likely to proceed (or fail to proceed) over the next few years.

Common Ground between AI 2027 & AI as Normal Technology asteriskmag.substack.com/p/common-groun… (interesting) #AI #future

woah, this is exciting -- curious to see results, congrats and good luck!

I'm impressed that you keep finding these!

October 28, 2025 - Public Sector Job Board The 73rd edition. Your source of tech and innovation jobs in government.

I can't think of a better resource today for those looking to learn about and/or break into civic tech than @kdyz.bsky.social's #PublicSectorJobBoard. I can't imagine it's at all a small lift—thank you Rebecca!

publicsectorjobboard.substack.com/p/october-28...

A screenshot of the title page of the Common App Call for Research Proposals, AY 2025-2026. The Executive Summary and main requirements for the Letter of Intent are visible. Exact text can be found at the link in the main post.

🚨Calling all education+social science researchers! 🚨

For the second time ever, Common App is hosting an open Call for Research Proposals to solicit innovative and rigorous research projects using our expansive (& still mostly untapped) data warehouse!
www.commonapp.org/files/DAR/Co...

We are slowly catching up to the #30DayMapChallenge!

In our day 3: polygons submission, @zhixuanqi.bsky.social questioned the boundaries and fuzziness of polygons with an animated map that invites us to think about the (not-so-well-defined) idea of neighborhoods.

So many nonsense ad hoc pipelines could be prevented by requiring that they work on synthetic data.

I tend to think of experiments as special cases of inference, since most of the problems I work on cannot be studied in experiments. But I get that many researchers see experiments as base analogy.

This was one of my favorite conferences last year

Will there eventually be an audiobook?

Congrats! Excited to take a look

Direct link to paper here: papers.ssrn.com/sol3/papers....

Have been waiting for this paper to come out ever since Hongyao told me about it -- more academics should be taking advantage of such open data to answer important questions

@sjgreenwood.bsky.social might have thoughts, based on work by Dave Rand and others

🧠⚙️ Interested in decision theory+cogsci meets AI? Want to create methods for rigorously designing & evaluating human-AI workflows?

I'm recruiting PhDs to work on:
🎯 Stat foundations of multi-agent collaboration
🌫️ Model uncertainty & meta-cognition
🔎 Interpretability
💬 LLMs in behavioral science

I’m recruiting students this upcoming cycle at UIUC! I’m excited about Qs on societal impact of AI, especially human-AI collaboration, multi-agent interactions, incentives in data sharing, and AI policy/regulation (all from both a theoretical and applied lens). Apply through CS & select my name!

Excellent report on experiences of @guidoimbens.bsky.social & Mary Wootters co-teaching "Causality, Decision Making, and Data Science" to undergrads at Stanford fall 2024: hdsr.mitpress.mit.edu/pub/uynpjlow... Course material here: stanford-causal-inference-class.github.io

yeah, happy to share! The student-facing instructions are here: orie5355.github.io/Fall_2025/pr..., and if you shoot me an email and I can share the non-student facing parts. One of our goals this year is better documentation, and I'd love to make this a generally available thing

I ...rolled my own, since I host multi-agent competitions (two teams go head-to-head over 2.5k timesteps. Over the years, we've automated as much as possible, using github classroom and autograding to check package compatibility, and scripts to pull repos onto our server

Haha sorry

The @stechlab-labels.bsky.social labeler is indeed very useful to weed out who to follow

What's wrong with Cornell Tech?! :)