Progress in academia

We're looking for a new colleague at @amlab.bsky.social: Assistant Professor in AI for Science 🔬🤖 World-class ML research, Amsterdam's thriving AI ecosystem (ELLIS, startups, big tech), and some of the best academic labor conditions in Europe ❤️ Deadline: May 30 👉 werkenbij.uva.nl/en/vacancies...

- The bitter lesson: Richard Sutton's view on AI - The butter lesson: more butter makes better food @gracekind.net - The batter lesson: crêpes are better than pancakes - The better lesson: AI can potentially improve teaching - The botter lesson: genAI takes over social media

In this incredibly detailed and gracious review of “The Irrational Decision,” @himself.bsky.social situates the book in the web of intellectual history and the war between the AI enthusiasts and skeptics.

Writing forces your brain to coordinate memory, reasoning, and meaning-making simultaneously. Every time you write, you rewire toward clearer thinking. Every time you let an LLM do it, you rewire toward consumption.

🚨 Happy to announce CVPR@Paris'26 which will take place on June 1st in Paris. The goal of the event is to share a little bit of the conference before it happens. We will have poster sessions as well as several plenary talks by world-class speakers. info: cvprinparis.github.io/CVPR2026InPa...

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Great post about how and why do science (and winning a best paper award is not the goal).

A day in the life of… youtu.be/T4Upf_B9RLQ?...

"In the interest of time I should agree with you. But that would just not be me." -every faculty meeting I've been to

Bibliography cleanup is known to be harder than AGI. Same with successfully connecting a laptop with a projector. It's what we humans will be doing long after the robot takeover. 😇

With some trepidation, I'm putting this out into the world: gershmanlab.com/textbook.html It's a textbook called Computational Foundations of Cognitive Neuroscience, which I wrote for my class. My hope is that this will be a living document, continuously improved as I get feedback.

I'd like to propose the following norm for peer review of papers. If a paper shows clear signs of LLM-generated errors that were not detected by the author, the paper should be immediately rejected. My reasoning: 1/ #ResearchIntegrity

Inspiring, though provoking, disagreeable 😉. Great to have @lakens.bsky.social as a keynote at our third metascience for Machine Learning workshop metascienceforml.github.io

Interesting take on the role of publication venues.

Riffing on Ed Leamer’s “sinning in the basement,” I ponder a theoretical reformation in machine learning. (There are ImageNet scatterplots, IYKYK.)

Interesting initiative; started by frustrated scientist; for frustrated scientists.

Meet @dimadamen.bsky.social, Prof of Computer Vision at the @bristoluni.bsky.social 🏴󠁧󠁢󠁥󠁮󠁧󠁿 & ELLIS Fellow working in Multimodal Learning Systems. She aims to inspire more women to lead in #AI by highlighting more role models. Discover her career milestones and goals for the field. #WomenInELLIS

This ambitious line of work is a great example of empirical theory in deep learning! I think we need more empirical theory in ML/DL (in contrast what ML people call 'theory', which is math, but not empirical 🙂). Metascience for ml 🙂 metascienceforml.github.io

Now you can either do 2 things: Adding more coils, bigger magnets, an iron core, and engineering all that until you get a useful product that changes the world. Or you can try to understand what is going on, like Michael Faraday did and as later James Clerk Maxwell formalized. I want the latter.

Do scientific papers need to be boring? 🤔

In 2016 Hinton predicted that AI would replace all radiologists in five years. Ten years later, why hasn't it happened? This post is a great explainer. www.understandingai.org/p/ai-isnt-re...

A simple argument for equivariance at scale: 1) At scale, token-wise linear layers dominate compute. 2) Token-wise linear equivariant layers implemented in the Fourier domain are block-diagonal and hence fast.

😱😱😱 @jvgemert.bsky.social are you ok? You could have told us all you were a ghost from the beginning!👻

There are diminishing returns. Stop trying to improve review quality by excessive extra work. Remember the irreducible Bayes Error: If the task has inherent subjectivity, it will not help to get better quality measurements.

🚀 Today we're launching the 'Night Science Institute', a non-for-profit organization to lead a cultural shift in science! You may say we're dreamers 😉, but we think we're not the only ones. Perhaps today you will join us to make the Day Science and Night Science parts of the process live as one!

Guilty 😅

Great post on anti-bureaucracy, machine learning theory, and pull requests.

The biggest publishers pulled profit margins in 2023 that rival Big Tech. And they still charge you to publish and your library to read. When are we going to start seriously thinking of alternatives to reform #PeerReview? 🧪 #SciPub #AcademicPublishing

The NeurIPS paper checklist corroborates the bureaucratic theory of statistics.

Our computer vision textbook is now available for free online here: visionbook.mit.edu We are working on adding some interactive components like search and (beta) integration with LLMs. Hope this is useful and feel free to submit Github issues to help us improve the text!

Instead of meeting in the home country, we do it in a country far away 🙂

"Academia is built upon a foundation of review. It is messy, decentralized collective decision making that selects a group of people and their writing into a canon of thought."

Worth your time to read this characteristically thoughtful blog post by Leon Bottou on LLM research. leon.bottou.org/news/two_les...

Amazing work on evaluating LLM evaluation.

Evaluating evaluation 🙂

Uhhh, hi! It's me, Bookshop.org, a place to buy books online where every purchase financially supports indie bookstores instead of some billionaire.

⏳Only 1 day left to submit your reviews! ⚠️Late or careless reviews won’t be taken lightly — authors of such reviews risk having their own submissions desk rejected. Please be fair and responsible!🙂

In today's episode of the Night Science Podcast we talk with Martin Schwartz from Yale about the importance of stupidity in science: while learning science makes you feel smart, true scientific discovery often involves feeling stupid, because it means venturing into the unknown.

Don’t be that person—take your #ICCV2025 reviewer responsibilities seriously.

After a short era in which people questioned the value of academia in ML, its value is more obvious than ever. Big labs stopped publishing the minute commercial incentives showed up and are relentlessly focused on a singular vision of scaling. Academia is a meaningful complement, bringing... 1/2

🔥🔥🔥 CV Folks, I have some news! We're organizing a 1-day meeting in center Paris on June 6th before CVPR called CVPR@Paris (similar as NeurIPS@Paris) 🥐🍾🥖🍷 Registration is open (it's free) with priority given to authors of accepted papers: cvprinparis.github.io/CVPR2025InPa... Big 🧵👇 with details!

arxiv.org/abs/2503.15156 This is a very interesting paper about locally anchored implicit neural representation. To me, it looks more like a joint keypoints detector and descriptor trained for image reconstruction. I wonder if these approaches could be tuned for geometric tasks or retrieval tasks.

*Please repost* @sjgreenwood.bsky.social and I just launched a new personalized feed (*please pin*) that we hope will become a "must use" for #academicsky. The feed shows posts about papers filtered by *your* follower network. It's become my default Bluesky experience bsky.app/profile/pape...

Get to know @gulvarol.bsky.social, Senior Researcher at École des Ponts ParisTech 🇫🇷 She's an ELLIS Scholar, member of ELLIS Unit Paris, former winner of the ELLIS PhD Award. Her research covers computer vision, vision & language, human motion generation & sign languages. #WomenInELLIS

I'm proud to have been awarded a prestigieus VICI grant (€1.5m) for data efficient AI foundation models. AI with less data breaks our dependency on third party companies, and, allow curatable datasets for bias, privacy, and transparency. www.tudelft.nl/en/2025/tu-d...

I love this type of exploratory, elegant, research! What would it take to generalize these findings to a testable hypothesis?

Do large language models develop "emergent" models of the world? My latest Substack posts explore this claim and more generally the nature of "world models": LLMs and World Models, Part 1: aiguide.substack.com/p/llms-and-w... LLMs and World Models, Part 2: aiguide.substack.com/p/llms-and-w...

As someone who has reported on AI for 7 years and covered China tech as well, I think the biggest lesson to be drawn from DeepSeek is the huge cracks it illustrates with the current dominant paradigm of AI development. A long thread. 1/