Frank Hutter

The tabular data science revolution is really here now! I’m thrilled to introduce *TabPFN Scaling Mode*, removing TabPFN’s previous limit on dataset size. The plot below shows scaling results for the biggest dataset we have tried so far (subsamples of 100k and 1M, and the full 10M rows / data points). While we’ve only benchmarked up to 10M rows (a 100x increase in the 3 weeks since the release of TabPFN-2.5!), the results indicate that we can just scale to any dataset size now 🚀 🧵1/4

@NandoDF @bing @Azure @satyanadella Best of luck in what’s to come next @NandoDF!

It’s my last day at Microsoft AI. It was a privilege to be part of such a talented team that achieved so much in such a short time. I’m super grateful to the @bing and @Azure teams too. @satyanadella impressed me a lot: A leader that taught us to care not only about Sota, but about delivering value to communities. I believe Microsoft AI is now in a strong place and have the talent and resources to deliver value for their users in many years to come. Thank you, so long, and looking forward to my next AI adventure too, after a precious break with my family in the Argentinian Andes.

@prior_labs @UniFreiburg @ELLISInst_Tue Here is the team that made this happen!

4/4 Huge thanks to everyone at @prior_labs, @UniFreiburg, @ELLISInst_Tue and the community that got us here. Let’s go and take things to the next level! Founders’ statement: priorlabs.ai/blog-posts/pri…

Today it is official: our acquisition by SAP has closed. Prior Labs continues as an independent frontier AI lab - same team, same offices, same mission, open models, backed by €1B+. What changes? The scale and the planning horizon. 🧵 1/4

Deep learning transformed how machines understand text and images. But the data that actually runs most enterprises, the rows and columns inside spreadsheets and databases, has largely missed that revolution. For decades, structured data has powered decisions across healthcare, finance, and business, yet it's been analyzed using many of the same approaches long after AI advanced everywhere else. That is beginning to change. A new generation of Tabular Foundation Models is bringing frontier AI to structured data, delivering faster, more accurate predictions without the task-specific training traditional models require. It's already powering real-world applications, from early disease detection to financial risk modelling, and redefining what's possible with enterprise data. This July 8, @FrankRHutter, Founder & CEO at @Prior_Labs, takes the Grace Hopper Stage for his keynote, "The Foundation Model Revolution for Structured Data." Drawing on the latest advances behind Prior Labs' TabPFN, he'll explore where the technology stands today, why this represents a fundamental shift for enterprise AI, and what's next for the future of structured data. If foundation models transformed text and images, what happens when they finally transform the data your business actually runs on? Final ticket price increase on July 2. 🔗 Secure your ticket:  hubs.li/Q04mY1fL0

Model report: priorlabs.ai/reports/tabpfn… Get started here: priorlabs.ai/tabpfn

Available three ways: 👉 Open weights for research & internal evaluation 👉 API with TabPFN-3-Plus & Thinking Mode 👉 Enterprise licensing (incl. AWS SageMaker, Azure AI Foundry, on-prem) Model report in replies. 🧵 5/5 With ❤️ from Prior Labs

The data science revolution is here now. TabPFN-3 is live, taking tabular foundation models to enterprise scale 🤩 1M training rows on a single H100. No training. No tuning. Load and predict. 🧵 1/5 #tabpfn #tabularfoundationmodels #priorlabs

Huge news: @prior_labs has signed a definitive agreement to be acquired by @SAP. €1B+ invested over four years to build a globally-leading frontier AI lab for structured data — in Europe, in the open. Independent entity. Same team, same mission, same open models. A massive boost to what we can do. The mission just got accelerated. Founders’ statement: priorlabs.ai/blog-posts/pri… (Deal subject to regulatory approval; terms not disclosed.)

This is a special moment for us at @prior_labs. I’ve followed @ylecun’s work since the start of my career. His relentless focus on "what’s next" in AI has always been an inspiration. Today, I’m proud to say that he is joining us as a scientific advisor to help build the future of Tabular Foundation Models. Yann understands that while LLMs have captured the world's attention, they have severe limitations. The vast majority of the world's data is tabular and LLMs are terrible with statistics and numbers. Our model, #TabPFN, fills this void, and the progress we are seeing is exponential. A warm welcome to the team, Yann. It’s an honor to work with you alongside @bschoelkopf, Madelon Hulsebos, and @SamuelMullr on this powerhouse board. #DeepLearning #DataScience #TabularData #AI

4/4 We’re currently working directly with customers to run TabPFN-2.5 Scaling Mode on their data. If you’re interested, please contact sales@priorlabs.ai to get on the waitlist.

3/4 More details in our blog post: priorlabs.ai/technical-repo…

The tabular data science revolution is really here now! I’m thrilled to introduce *TabPFN Scaling Mode*, removing TabPFN’s previous limit on dataset size. The plot below shows scaling results for the biggest dataset we have tried so far (subsamples of 100k and 1M, and the full 10M rows / data points). While we’ve only benchmarked up to 10M rows (a 100x increase in the 3 weeks since the release of TabPFN-2.5!), the results indicate that we can just scale to any dataset size now 🚀 🧵1/4

Update: TabPFN-2.5 is actually the SOTA model on all of TabArena (which has datasets with up to 100k training data points). In a single forward pass, TabPFN-2.5 outperforms all other models, even if you tune them for 4 hours. We built and previously evaluated TabPFN-2.5 for up to 50k data points (and 2k features) and were kind of surprised that it's SOTA up to 100k 🙂 👉 TabPFN-2.5 webinar tomorrow: app.livestorm.co/p/21526e44-406… 👉 Model report on arXiv: arxiv.org/pdf/2511.08667