Very excited to introduce locality alignment, an efficient post-training algorithm to improve your ViTs + VLMs, essentially for free🚀 Local align = new self-supervised objective ensuring that encoder captures fine-grained spatial info. No new data needed. Here's the idea 1/3

Can machine learning models predict their own errors 🤯 ? In a new preprint w/ Apple collaborators Aravind Gollakota, Parikshit Gopalan, Charlotte Peale, and Udi Wieder, we present a theory of loss prediction and show an equivalence with algorithmic fairness! A thread (1/n):

We can now fine-tune the 7B OpenVLA model for 50 Hz control! 🤖 Paper: openvla-oft.github.io Code: github.com/moojink/openvl…

No one becomes a clinician to do paperwork, but it's becoming a bigger and bigger administrative burden, taking time and attention away from actually treating and supporting patients. That’s why we’re introducing Microsoft Dragon Copilot, the industry’s first AI assistant for

This is an incredible resource on #AIAgent !

Meet the recipients of the 2024 ACM A.M. Turing Award, Andrew G. Barto and Richard S. Sutton! They are recognized for developing the conceptual and algorithmic foundations of reinforcement learning. Please join us in congratulating the two recipients! bit.ly/4hpdsbD

An introductory talk by Christopher Manning Christopher Manning on “Large Language Models in 2025 – How much understanding and intelligence?” at the Workshop on a Public AI Assistant to Worldwide Knowledge at Stanford University, covering 3 eras of LLMs, RAG, Agents, DeepSeek-R1, using LLMs, ….

🚨Announcing our #ICLR2025 Oral! 🔥Diffusion LMs are on the rise for parallel text generation! But unlike autoregressive LMs, they struggle with quality, fixed-length constraints & lack of KV caching. 🚀Introducing Block Diffusion—combining autoregressive and diffusion models

New paper - Transformers, but without normalization layers (1/n)

Happy to share our new paper out in #EHJIMP! ❤️ In this study, we measured 3D Left Atrial Phasic Strain from 4D CT to identify non-paroxysmal AF and predict AF recurrence after ablation. Check it out #OpenAccess: doi.org/10.1093/ehjimp…

Spatial reasoning is a major challenge for the foundation models today, even in simple tasks like arranging objects in 3D space. #CVPR2025 Introducing LayoutVLM, a differentiable optimization framework that uses VLM to spatially reason about diverse scene layouts from unlabeled

Can LLMs learn to reason better by "cheating"?🤯 Excited to introduce #cheatsheet: a dynamic memory module enabling LLMs to learn + reuse insights from tackling previous problems 🎯Claude3.5 23% ➡️ 50% AIME 2024 🎯GPT4o 10% ➡️ 99% on Game of 24 Great job Mirac Suzgun w/ awesome

🎉 Proud moment! I-SENSE Faculty Fellow Dr. Behnaz Ghoraani, a leader in biomedical data science & smart health tech, is FAU’s Scholar of the Year! Honored at the 56th Honors Convocation for groundbreaking research improving global health. 🌍❤️ #FAU #Innovation #GoOwls

Happening now: Stanford Biodesign New Arrhythmia Technologies Retreat at #SanDiego ! Opening remarks from Paul J Wang, MD Sanjiv Narayan . Great talks coming up!

Why do we need #AI in #cardiacEP ? AI models can do tasks beyond humans' capability. Learning features unknown to humans, forecasting, automated remote monitoring, etc. Need more collaborative efforts to bring AI into practice. Great talk by Tina Baykaner! Stanford Biodesign

Great reminders from Sanjiv Narayan re: Mapping in the current era - we still have work to do! * EGMs ≠ Action Potentials * How to we compare across #AI models? Very tough to do * with implementation of AI, outcome & workflow need better synchronization #StanfordBiodesign2025

Gemini powers our multimodal health research! 💙 In our new paper on multimodal AMIE, we're pushing conversational diagnostic AI beyond text to handle images such as skin photos, ECGs, and clinical docs, which provide crucial context in healthcare. Blog: goo.gle/42D0QcB

Curious about optical mapping techniques for cardiac research? Here's a quick video demonstrating the optical mapping recording and analysis of mouse atrial electrical activity (Ca²⁺ and AP). @MappingLab #cardiotwitter #electrophysiology #Cardiology #calcium #actionpotential

Flow Matching (FM) is one of the hottest ideas in generative AI - and it’s everywhere at #ICML2025. But what is it? And why is it so elegant? 🤔 This thread is an animated, intuitive intro into (Variational) Flow Matching - no dense math required. Let's dive in! 🧵👇

Check out our state-of-the-art open weights MedGemma multimodal model for making sense of longitudinal EHR data as well as medical text and medical imaging data in various modalities (radiology, dermatology, pathology, ophthalmology, etc.) See the blog post linked below! ⬇️