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SUMMARY:The State of Tabular AI 2026: scikit-learn\, Tabular Foundation Mo
 dels\, and Agentic Data Science - Gaël Varoquaux\, Madelon Hulsebos
DTSTART;TZID=Europe/Paris:20261125T100500
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DTSTAMP:20261111T073051Z
UID:pretalx-compute-paris-2026-ETHXZX@pretalx.com
DESCRIPTION:Tables are the ground truth of the enterprise\, yet for years 
 AI’s progress on text and images dominated the headlines. Probabl’s St
 ate of Tabular AI Report 2026 argues that AI for tabular data deserves rec
 ognition as a category in its own right. The report maps the innovations t
 hat shaped it this year based on quantitative analysis of research and ind
 ustry trends and interviews with researchers\, open source developers\, an
 d labs.\nThis session begins with a 10-minute presentation by Gaël Varoqu
 aux\, who shares the report’s main findings. First\, open source and ope
 n science are driving innovation in Tabular AI\, from the scikit-learn eco
 system to tabular foundation models. Second\, new tools like tabular found
 ation models and agentic frameworks are expanding the data scientist’s t
 oolbox rather than replacing it. Third\, as data scientists increasingly a
 dopt agents in their workflows\, the bottleneck is shifting from pipeline 
 building to validation.\nThen\, Gaël is joined by Madelon Hulsebos for a 
 20-minute discussion about open questions in Tabular AI research and innov
 ation: where tabular foundation models still fall short on real-world data
 \, how to evaluate data science agents\, and how to support the open scien
 ce flywheel of Tabular AI.
LOCATION:Auditorium
URL:https://pretalx.com/compute-paris-2026/talk/ETHXZX/
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