iiinova — where your digital self keeps evolving

🧠 TextEncoder is now LLMEncoder -- clearer name, same transformer embeddings

Reposted by Gaël Varoquaux

📊 DataOp reports now link to your source code and show docstrings -- can be generated without executing calculations

Reposted by Gaël Varoquaux

⚡ The SessionEncoder is now up to 15x faster

Reposted by Gaël Varoquaux

🔍 describe_transformations() -- can now print a plain text explanation of what TableVectorizer and Cleaner did to each column

Reposted by Gaël Varoquaux

💾 Persistent caching for DataOps -- pipeline steps can now be cached across runs

Reposted by Gaël Varoquaux

🆕 CatEncoder -- OneHotEncoder + TargetEncoder, two encoders combined in a single column transformer to deal with columns with many infrequent classes

Reposted by Gaël Varoquaux

🫂13 new contributors helped with this release!

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Also in this release: faster construction of deep DataOps, ToCategorical for numeric columns, and more!

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✨ Skrub 0.11 has been released ✨ Full changelog: skrub-data.org/stable/CHANG... Heads-up: skrub 0.11 requires Python ≥ 3.11 and scikit-learn ≥ 1.5.2. Highlights in thread ⤵️

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threadpoolctl/README.md at master · joblib/threadpoolctl

The README now also includes a section about how to empirically assess the subtle semantic variations of various BLAS and OpenMP runtimes: github.com/joblib/threa...

github.com

Python helpers to limit the number of threads used in native libraries that handle their own internal threadpool (BLAS and OpenMP implementations) - joblib/threadpoolctl

Reposted by Gaël Varoquaux

Mitigating this problem is needed to unlock the full value of free-threading Python, especially for @scikit-learn.org workloads that often nest BLAS calls (via NumPy, SciPy or PyTorch) and OpenMP calls (via Cython) under Python level threads (typically via joblib).

Reposted by Gaël Varoquaux

Oversubscription problems typically happen when nesting BLAS or OpenMP calls under Python threads: naively spawning 10 Python threads that themselves spawn 10 BLAS threads each results in 100 starving threads on a 10 cores CPU.

Reposted by Gaël Varoquaux

itamarst.hachyderm.io.ap.brid.gy

This release includes several contributions by itamarst.hachyderm.io.ap.brid.gy from @quansight.com. in collaboration with myself & others at @probabl.ai. It provides tools to inspect the semantics of native threadpools in various environments so as to be able to mitigate oversubscription problems.

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Sean Carroll @seanmcarroll.bsky.social · 10/09/2026

threadpoolctl 3.7.0 is out. This library is a utility used by @scikit-learn.org and others to coordinate the levels of thread-based parallelism in native libraries such as BLAS implementations and OpenMP runtimes used by Python libraries such as NumPy, SciPy, PyTorch and scikit-learn.

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My thoughts on existential risk: * Humanity isn't going to be wiped out any time soon. * Negligible chance that AI by itself causes catastrophic damage to humanity (millions dead). * Some nontrivial chance that human beings will leverage AI to help them do something catastrophically harmful.

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Gaël Varoquaux @gaelvaroquaux.bsky.social · 06/09/2026

AI Safety & Industry Thinking 📖: a personal anecdote The recent cyber-security screw-ups with AI-mediated attacks on third parties reminded me of a discussion a few years ago... Story time! 👇

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Skrub @skrub-data.bsky.social · 01/09/2026

🐞 Bug fix release incoming 🐛 Version 0.10.1 of skrub is now live! In this release, we fixed a Cloudpickle import error that could be triggered by some updated dependencies, along with some other improvements. Release post: github.com/skrub-data/s... 1/4

github.com

Release 0.10.1 · skrub-data/skrub

🌟 Skrub 0.10.1 has been released 🌟 Main features When a cross-validation splitter has been passed to .skb.mark_as_X(), it it now possible to select a specific split from it when calling .skb.train...

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Erin J. Wamsley 🧠📈😴 @wamsleylab.bsky.social · 01/09/2026

Oh. my. god. The biggest scientific publishers are collecting nearly $4 BILLION A YEAR in author fees. This is absurd. We've got to break free of this system. If everyone would just agree to it, we could just post all our new papers on bsky and it wouldn't cost anything. Or something. But not this.

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jamilahmedai.bsky.social @jamilahmedai.bsky.social · 01/09/2026

Stanford's visiting scholar forums or the SUPost classifieds are usually great for short October sublets around Palo Alto/Menlo Park. Reposting to help spread the word.

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Gaël Varoquaux @gaelvaroquaux.bsky.social · 31/08/2026

🏠 Acomodation around Stanford: One of my very brillant students is visiting Stanford for a few weeks in October (dates to be defined). Would people have suggestions for housing for her that wouldn't be affordable? She is very reliable and I can absolutely recommend her. Thanks

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Gaël Varoquaux @gaelvaroquaux.bsky.social · 08/08/2026

Les lois contraignant les véhicules lourds pour protéger les véhicules légers (stationnement, distance de déplacement) ne sont pas appliquées, des forces de l'ordre refusant de verbaliser. Mais on invente de nouvelles lois contraignant les véhicules légers. ⚠ aux verbalisations à sens unique

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Gaël Varoquaux @gaelvaroquaux.bsky.social · 08/08/2026

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Compute! Paris @computeparis.bsky.social · 07/08/2026

At #ComputeParis, Riccardo Cappuzzo will show how to build complex preprocessing pipelines with skrub's Data Ops module, showcasing it for varying examples from churn prediction over energy usage forecasting, to image processing. skrub-data.org/stable/ compute.events/paris2026 🛸

compute.events

Compute! Paris 2026

Understanding your tools and algorithms is what gives you agency in a digital world. Paris, November 25–26, 2026.

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Compute! Paris @computeparis.bsky.social · 07/08/2026

Tabular data powers a huge share of machine learning applications, bringing with it the challenge of turning fragmented, messy datasets into reliable features. The Python library #skrub for "Machine learning with dataframes", part of the widely used scikit-learn ecosystem, tackles this challenge.

skrub-data.org

Skrub

Machine learning with dataframes

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Christophe Michel @christopheml.fr · 06/08/2026

"Oui mais c'est bien de porter un casque", oui mais ça ne veut pas dire qu'il faut le rendre obligatoire pour autant. Ce que de nombreux pays plus en avance que nous sur le vélo ont montré, c'est que ce qui réduit les accidents ce sont les infrastructures et un meilleur partage de la voirie.

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Christophe Michel @christopheml.fr · 06/08/2026

100% une décision faite pour plaire aux boomers (leur autre grande marotte étant d'immatriculer les vélos et de leur imposer un permis), qui coûte 0 à l’État, permet de faire plus de répression stupide (comme l'interdiction des écouteurs) et n'améliore qu'à la marge la sécurité des cyclistes.

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Ben Recht @beenwrekt.bsky.social · 24/07/2026

Now that the rich and powerful people are calling for open-weights models, it's time to pressure them to be legitimately brave and back open-corpus models.

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Gaël Varoquaux @gaelvaroquaux.bsky.social · 02/07/2026

A fun podcast with Maxime Gabella about our dreams about AI. The next frontier of AI is building agents that use statistical learning to tackle problem-specific challenges from data. Agents come with promises, but they need a statistical harness, as @probabl.ai's www.youtube.com/watch?v=cNpv...

youtube.com

Can AI Become a Real Data Scientist? | Gaël Varoquaux on scikit-learn, Probabl & Scientific Judgment

YouTube video by Maxime Gabella

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ELLIS @ellis.eu · 30/06/2026

🏹 Job alert: Postdoc on Tabular Foundation Models at Inria 📍 Palaiseau 🇫🇷 ⏰ 20 August 🔗 bit.ly/4eN1j0N

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Gaël Varoquaux @gaelvaroquaux.bsky.social · 29/06/2026

🧑‍💻🧑‍🏫 I'm recruiting a post-doc to work on Tabular Foundation Models, one of the hotest topics in AI, where we are at the leading edge team.inria.fr/soda/files/2... This is an opportunity to develop the next-level tabular AI, blending deep learning and tables.

team.inria.fr

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Manuel Mendoza @longchrom.bsky.social · 22/06/2026

This article in Le Monde about French research in general and the CNRS in particular has a few depressing graphs www.lemonde.fr/sciences/art...

The graph highlights a growing divergence between Germany and France:

* In the mid-1990s, France and Germany spent similar shares of GDP on R&D.
* Germany subsequently increased its R&D investment by about 1 percentage point of GDP.
* France’s R&D effort remained largely stagnant.
* By 2023, Germany spends 3.15% of GDP on R&D compared with 2.18% in France, a gap of nearly 1 percentage point of GDP.
* France is also well below the OECD average (2.93%).

The figure therefore illustrates that France has fallen behind both Germany and the OECD average in R&D intensity over the past three decades.

Sources listed on the graphic: OECD database, UNESCO, ANR, ERC; infographic by Le Monde.

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Gaël Varoquaux @gaelvaroquaux.bsky.social · 22/06/2026

You're only a real statisticien if you can say "Heteroscedasticity" without flinching

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Ultimes scories @panettonepazzo.bsky.social · 21/06/2026

Vous avez systématiquement voté contre tout projet de loi écolo. Vous avez stigmatisé les militants en « eco-terroristes ». Vous avez coupé les crédits verts des budgets. Vous avez nommé des ministres pro énergies fossiles et pesticides. Vous avez parlé «d’écologie punitive». Ne venez pas pleurer

Capture d’écran d’un post X du HuffPost avec article et avec ce texte :

« On n’a pas été assez loin et assez vite » : La canicule oblige les macronistes à un rare mea culpa »

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scikit-learn @scikit-learn.org · 12/06/2026

🎉 Scikit-learn 1.9 released: ■Solid improvements to many existing estimators: faster, more stable, handling missing values, adding GPU support… ■Also, enhanced estimator displays in notebooks, ■And callbacks that enable progress bars or monitoring of convergence blog.scikit-learn.org/updates/rele...

blog.scikit-learn.org

scikit-learn release 1.9: better numerics, new core functionality

Author: Gael Varoquaux

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Olivier Grisel @ogrisel.bsky.social · 04/06/2026

The CfP deadline for Compute! Paris 2026 was extended to Sunday, June 7! Just a few days left to submit a proposal on Open Source scientific compute, data science, ML & AI topics. Conference dates and venue: November 25–26, 2026, Sorbonne Université · Paris compute.events/paris2026/cf...

compute.events

Call for Proposals — Compute! Paris 2026

Submit your talk proposal for Compute! Paris 2026. The Call for Proposals is open from April 15th to June 7th, 2026.

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Gaël Varoquaux @gaelvaroquaux.bsky.social · 26/05/2026

Modern AIs tackle different questions than data science on industry or scientific applications. Statistical thinking, front and center in data science, is often hidden in AI. But it’s just as crucial. And too often, we treat data science or AI as merely a programming exercise

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NeurIPS Europe @neuripseurope.bsky.social · 17/05/2026

FAQ on NeurIPS Europe: NeurIPS Europe is an official NeurIPS 2026 satellite event taking place in Paris, France, alongside the main conference in Sydney and the other satellite event in Atlanta. NeurIPS authors can present their papers at any of the three locations, subject to space availability.

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- It is now possible to pass arguments to the scorers in Data Ops, such as sample weights. - Diagrams for the Learner and parameter searches now include the full DataOp graph in their notebook repr. - It is now possible to find nodes by name in the DataOp graph.

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- fuzzy_join and Joiner now allow to choose the metric that should be used for matching. - ApplyToCols now has the exclude_cols parameter, to define which columns should not be transformed.

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- The TableReport now uses plot_distributions and compute_associations to control the distribution and association tabs respectively. - The cleaner now allows to control whether numeric-looking strings ("['1', '2', '3']") should be parsed to float.

Reposted by Gaël Varoquaux