iiinova — where your digital self keeps evolving

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Dan Goodman @neural-reckoning.org · 20/09/2026

I'm not sure I agree with @giorgio.gilest.ro's logic that this ends up with technofeudalism. Yes LLM-written papers are flooding journals, but that's because journals are and always were a bad tool for filtering for insight. Our response should be to try something different.

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Nicolas Audebert @nshaud.bsky.social · 03/08/2026

I'm burnt out of discussing "AI". I don't care for the press releases from big companies. I hate having to comment immediately. I dislike "hot takes". I'm worried we, as scientists, are losing touch with scientific values. We've become customers, salivating at ads marketed to investors. 1/15

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Dr. Martin Skrodzki @msmathcomp.bsky.social · 17/09/2026

Open Position for an Assistant/Associate Professor in Visual Analytics: careers.tudelft.nl/job/Delft-As.... Apply if you are excited about interactive exploration, analysis, and interpretation of complex data. Please also forward this position to anyone in your network who is interested.

careers.tudelft.nl

Assistant/Associate Professor in Visual Analytics

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Jan van Gemert @jvgemert.bsky.social · 18/09/2026

I never wanted to share my slides before the lecture because it ruins my Socratic teaching style 🍵 But.. I found out they are circling in the interwebs, so, I might as well share them myself then 🙂. Then at least they are up to date 😊. jvgemert.github.io/teach.html

jvgemert.github.io

teaching | Jan van Gemert

Academic website of Jan van Gemert, Computer Vision and Deep Learning research, TU Delft.

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Jan van Gemert @jvgemert.bsky.social · 14/09/2026

Our fifth workshop on Meta-science for Machine Learning is on Sept 22. metascienceforml.github.io Registration info in the link.

metascienceforml.github.io

Metascience for Machine Learning

A repository for collecting information about Metascience for machine learning.

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Jan van Gemert @jvgemert.bsky.social · 12/09/2026

A Delfie at the European Conference on Computer Vision #ECCV2026 :)

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Jan van Gemert @jvgemert.bsky.social · 09/09/2026

@eccv.bsky.social #ECCV2026 How can I organize which posters to see where? The app cuts off paper titles (ie: unreadable and unusable). The website's schedule is great, but has no poster IDs next to the titles. Will we get a handy hardcopy program, with titles, times, and ids?

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Evangelos Kazakos @ekazakos.bsky.social · 02/09/2026

Computer vision people, where are you??? 👀

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Victoria Bosch @initself.bsky.social · 28/08/2026

Are brains and artificial neural networks converging onto universal representations? There is a seductive idea making the rounds in NeuroAI / machine learning: train systems well enough, and they all converge on the same representation of reality (i.e. a unique world model). We have thoughts™ 1/n

cell.com

The Umwelt Representation Hypothesis: rethinking Universality

Recent studies reveal striking representational alignment between artificial neural networks (ANNs) and biological brains, leading to proposals that all sufficiently capable systems converge on univer...

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Jan van Gemert @jvgemert.bsky.social · 02/09/2026

#ECCV2026 Workshop on Empirical Theory: tracing back the causal relationships in our scientific papers. Untroubling the "troubling trends in machine learning scholarship" empiricaltheory.github.io @eccv.bsky.social

empiricaltheory.github.io

E.T. : Empirical Theory in Representation Learning

Phoning home to science

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ML for Science @ml4science.bsky.social · 06/08/2026

📢 We're hiring: Tenure-Track Professor for Philosophy of Machine Learning for Science @unituebingen.bsky.social! We're looking for an outstanding researcher with a strong profile in #philosophy and strong connections to #ML and #AI. Deadline: 30 Sept 2026; more info: uni-tuebingen.de/en/128980 1/3

This graphic displays the following text on a colored background: Open Position: Tenure-Track Professor of Philosophy of Machine Learning for Science. Application Deadline: September 30, 2026.

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Jan van Gemert @jvgemert.bsky.social · 31/07/2026

@vele.bsky.social @cscv-bot.bsky.social I love your arXiv bot ♥️. But.. reading it is difficult due to the author names coming first, so the most important thing is difficult to find: the paper title 🙂. If it was up to me, I would remove the author list completely 😁.

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Jan van Gemert @jvgemert.bsky.social · 24/07/2026

NeurIPS reviewers not liking understanding-based ML work? Consider submitting to our workshop: empiricaltheory.github.io - R1: Reject. Not state of the art. - R2: Reject. Just small toy datasets. - R3: Reject. After reading the paper it's trivial.

Empirical Theory in Representation Learning

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David Picard @davidpicard.eurosky.social · 07/07/2026

The E.T.👽 workshop submission is finally open! We aim at promoting scientific theory building in deep representation learning 2 tracks: 1p storyline & regular 14p full paper Deadline: Aug 1st 🖥️ empiricaltheory.github.io 📜 openreview.net/group?id=the... Let's do science! @eccv.bsky.social #ECCV

empiricaltheory.github.io

E.T. : Empirical Theory in Representation Learning

Phoning home to science

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Jan van Gemert @jvgemert.bsky.social · 13/07/2026

Understand-based research vs BOLD numbers. Submit your work to our ECCV workshop on Empirical Theory: empiricaltheory.github.io @davidpicard.eurosky.social @a-lucic.bsky.social m.loog, h.hung, h.pinson.

empiricaltheory.github.io

E.T. : Empirical Theory in Representation Learning

Phoning home to science

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European Conference on Computer Vision #ECCV2026 @eccv.bsky.social · 05/07/2026

The #ECCV2026 workshop page with links is now up! eccv.ecva.net/Conferences/...

eccv.ecva.net

2026 Workshops

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Jan van Gemert @jvgemert.bsky.social · 18/06/2026

Honered to get a selfie with our Netherlands Conference on Computer Vision (NCCV) keynote speaker! The brilliant @vickykalogeiton.bsky.social Two zealots of the Data efficiency church in the Religion of Scaling AI 🙏

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Aaron Hertzmann @aaronhertzmann.com · 10/06/2026

This piece brilliantly explains why it's not only unnecessary to take seriously the idea that LLMs are conscious, in some cases it is ethically irresponsible.

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Flavio Martinelli @flavioh.bsky.social · 10/06/2026

NEW PAPER. Why do larger networks train better? "Because they contain more candidate *sub*networks that can learn the task" → lottery tickets This popular explanation uses an appealing but misleading metaphor🧵 We propose an intuitive alternative grounded in theory: escape dimensions

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David Picard @davidpicard.eurosky.social · 09/06/2026

I'm taking this opportunity to make some advertising for an ECCV Workshop on empirical theory proposed by @jvgemert.bsky.social empiricaltheory.github.io Yes it's related. Think harder. You can connect the dots, I have faith in you 😉

empiricaltheory.github.io

E.T. : Empirical Theory in Representation Learning

Phoning home to science

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Melanie Mitchell @melaniemitchell.bsky.social · 21/05/2026

"Science is not simply a sequence of tasks that can be optimized....The scientific system thrives on inefficiency: redundant efforts, failed attempts, and divergent paths. These are not costs to be eliminated but sources of discovery." Excellent essay! ⬇️ www.science.org/doi/10.1126/...

science.org

Progression without progress

Progress in the use of artificial intelligence (AI) to advance scientific discovery has made it increasingly realistic to envision automated “end-to-end science” (ETES) systems: integrated pipelines t...

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Jesse Krijthe @jessekrijthe.bsky.social · 29/04/2026

We are hiring! We have exciting PhD opportunity to improve trustworthiness of causal inference at TU Delft, in collaboration with @gelovennan.bsky.social , in the Safe Causal Inference consortium. Apply now! #PhD #CausalInference #MachineLearning #Statistics careers.tudelft.nl/job/Delft-Ph...

careers.tudelft.nl

PhD Position Causal Inference & Machine Learning

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Jan van Gemert @jvgemert.bsky.social · 28/04/2026

Why is @eccv.bsky.social forcing unnecessary non-EU big tech on workshop organizers? Where should we uphold principles, if not even for top European publication venues?

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Oded Rechavi @odedrechavi.bsky.social · 17/04/2026

Progress in academia

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Erik Bekkers @erikjbekkers.bsky.social · 15/04/2026

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...

werkenbij.uva.nl

Vacancy — Assistant Professor in AI for Science (AI4Science)

Are you passionate about advancing Machine Learning by integrating insights from the natural sciences? Are you eager to bridge the 3rd (computational) and 4th (<span...

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Christian Wolf @chriswolfvision.bsky.social · 08/04/2026

- 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

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Ben Recht @beenwrekt.bsky.social · 06/04/2026

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.

open.substack.com

AI has limits, even if many AI people can't see them

On Ben Recht's fantastic new book

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Paul Graf @paulginva.bsky.social · 18/02/2026

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.

This editorial discusses the critical value of human-generated scientific writing in the era of large language models (LLMs), arguing that writing is essential to structured thinking and research comprehension.
Writing as Thinking: The act of writing structure's thoughts, sorting research data, and identifying the main message, unlike LLMs which may lack true understanding or accountability.
LLM Hallucinations: LLM-generated text requires rigorous verification because these models can produce incorrect information or fake references.
Human vs. AI Roles: While LLMs are useful tools for brainstorming, improving grammar, or overcoming writer's block, human researchers must maintain control to engage in the creative task of shaping a compelling narrative.

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David Picard @davidpicard.eurosky.social · 01/04/2026

🚨 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...

cvprinparis.github.io

CVPR@Paris 2026 June 1st

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Jan van Gemert @jvgemert.bsky.social · 11/03/2026

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

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Jessica Hullman @jessicahullman.bsky.social · 25/02/2026

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

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Melanie Mitchell @melaniemitchell.bsky.social · 04/02/2026

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. 😇

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Sam Gershman @gershbrain.bsky.social · 09/01/2026

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.

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Thomas Dietterich @tdietterich.bsky.social · 28/12/2025

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

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Jan van Gemert @jvgemert.bsky.social · 05/12/2025

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

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Jan van Gemert @jvgemert.bsky.social · 08/11/2025

Interesting take on the role of publication venues.

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Ben Recht @beenwrekt.bsky.social · 16/10/2025

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

argmin.net

Desirable Sins

Robustness of the holdout method and paths forward for machine learning theory.

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Jan van Gemert @jvgemert.bsky.social · 15/10/2025

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

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ELLIS @ellis.eu · 15/10/2025

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

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Jan van Gemert @jvgemert.bsky.social · 11/10/2025

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

metascienceforml.github.io

Metascience for Machine Learning

A repository for collecting information about Metascience for machine learning.

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David Picard @davidpicard.eurosky.social · 03/10/2025

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.

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Jan van Gemert @jvgemert.bsky.social · 03/10/2025

Do scientific papers need to be boring? 🤔

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Melanie Mitchell @melaniemitchell.bsky.social · 01/10/2025

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...

understandingai.org

AI isn't replacing radiologists

Radiology combines digital images, clear benchmarks, and repeatable tasks. But demand for human radiologists is at an all-time high.

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Georg Bökman @bokmangeorg.bsky.social · 18/09/2025

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.

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David Picard @davidpicard.eurosky.social · 15/09/2025

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

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Jan van Gemert @jvgemert.bsky.social · 01/08/2025

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.

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