Jure Leskovec

🚀 I'm excited to announce the Stanford Data-Centric AI Workshop 2026 (aka the Stanford Graph Learning Workshop), happening Tuesday, November 3, 2026 at @Stanford University (with online livestream). Free registration! Submit a poster. 📍

This year's workshop will spotlight three fast-moving frontiers in data-centric AI:
-- AI Foundations — Making frontier models fast and scalable
-- AI for Science and Biology — Agents and foundation models across the scales of biology
-- Relational and Tabular Foundation Models — Learning directly on the structured data that runs the world

We're bringing together Stanford researchers and industry partners for a full day of research talks, case studies, and collaborative discussion. Whether you're working in industry, academia, or startup land, there will be something to spark your curiosity and drive your work forward.

🔍 Want to share your work? Our Call for Posters and Demos is also open now.

✅ Register now (free): snap.stanford.edu/graphlearning-…

📅 Save the date: Nov 3, 2026

🦍 Memorilla treats memory as a modality for LLMs. Memorilla turns everything a frozen LLM needs to remember into just 16 memory tokens. It uses up orders of magnitude fewer tokens while being faster and more accurate than full context inference. 🎯 Pushes the Pareto frontier over RAG and agentic memory in personalization, long-document and knowledge QA.

🚀 It's time! The Stanford Data-Centric AI Workshop 2026 is kicking off NOW!

Join us for a full day of research talks, case studies, and community connection — all centered around this year's themes:

⚡ AI Foundations – making frontier models fast and scalable
🧬 AI for Science and Biology – agents and foundation models across the scales of biology
🔗 Relational and Tabular Foundation Models – learning directly on the structured data that runs the world

🎥 Tune in live: youtube.com/live/xQJEsCH0k…

📍 Stanford University | 🕗 Nov 3, 2026 | 8:30 AM – 6:00 PM PT

📢 The Full Schedule for the Stanford Data-Centric AI Workshop 2026 is Here!

We have an exciting lineup of speakers from industry and academia, including:

🔹 @SAP – semantics-aware foundation models for enterprise data
🔹@NVIDIA – tabular foundation models
🔹 Prof. @tatsu_hashimoto (@Stanford) – data-efficient language modeling
🔹 Prof. @james_y_zou (@Stanford) – learning a physiology foundation model

They are joined by Stanford researchers presenting new work across AI Foundations, AI for Science and Biology, and Relational and Tabular Foundation Models, plus a poster slam and poster sessions over lunch and at the evening happy hour.

📅 Tuesday, November 3, 2026 | 8:30 AM – 6:00 PM PT
📍 Stanford University + Online
🔗 Full schedule & free registration: snap.stanford.edu/graphlearning-…

See you next week!

RT-J is a System 1 model for structured data.