The hot topic at #ICCV2025 was World Models. They come in different flavors — (interactive) video models, neural simulators, reconstruction models, etc. — but the overarching goal is clear: Generative AI that predict and simulate how the real world works.

This was my experience in grad school, and now I've seen some evidence to suggest a trend 🤔

Our new paper in AJRCCM shows how AI & 5.5M+ MRI slices from 12K kids can predict brain outcomes in children who snore. Smaller upper airway volume = lower cognition + less gray matter. #ENT #PedsENT #DeepLearning #MedicalAI https://t.co/nuzFVJnVml

Really excited for the Flower AI Day in SF and the Decentralized AI Hackathon at Stanford this week 🌻. See ya'll soon!! #flwr #flower #sanfrancisco #stanford

Flower AI Day: Open-source Decentralized Superintelligence is here September 25 @SHACK15sf -- San Francisco Tickets and info: https://t.co/m3LTjlbkeg Speakers: @sarahookr (ex-@Cohere), @ce_zhang (@togethercompute/ @UChicago), @joespeez (@meta), @daniel_janes (@flwrlabs),

Introducing our first set of Llama 4 models! We’ve been hard at work doing a complete re-design of the Llama series. I’m so excited to share it with the world today and mark another major milestone for the Llama herd as we release the *first* open source models in the Llama 4

Course material for an MIT class "Introduction to Flow Matching and Diffusion Models", looks great if you want a principled and hands on understanding of diffusion models/flow matching

President of OpenAi, Greg Brockman shares the way to create a perfect prompt:

This is interesting as a first large diffusion-based LLM. Most of the LLMs you've been seeing are ~clones as far as the core modeling approach goes. They're all trained "autoregressively", i.e. predicting tokens from left to right. Diffusion is different - it doesn't go left to

7. OpenAI launched Deep Research, a new Pro ChatGPT feature that performs in-depth web research, analyzing text, images, and PDFs to deliver detailed reports with citations in under 30 minutes.

This paper is wild - a Stanford team shows the simplest way to make an open LLM into a reasoning model. They used just 1,000 carefully curated reasoning examples & a trick where if the model tries to stop thinking, they append "Wait" to force it to continue. Near o1 at math.

Manim: Python library for math animations

Our first short course with @AnthropicAI! Building Towards Computer Use with Anthropic. This teaches you to build an LLM-based agent that uses a computer interface by generating mouse clicks and keystrokes. Computer Use is an important, emerging capability for LLMs that will let

Are you writing an ICLR paper, and wondering... * What level of detail should the background have? * Why do people read related work? * How do I convey convincing results? I have some mostly satisfactory answers to these questions. https://t.co/CtowMH95lT

Introducing Meta Segment Anything Model 2 (SAM 2) — the first unified model for real-time, promptable object segmentation in images & videos. SAM 2 is available today under Apache 2.0 so that anyone can use it to build their own experiences Details ➡️ https://t.co/eTTDpxI60h

Project that blew my mind a bit earlier and I still think about often: A Trustworthy, Free (Libre), Linux Capable, Self-Hosting 64bit RISC-V Computer https://t.co/ku0TapR1Et This is an attempt to build a *completely* open source computer system, both software AND hardware.

I am excited to be giving a 4-hour tutorial on "Pretraining and Finetuning LLMs from the Ground Up" at the @SciPyConf conference in 5 days! This tutorial is aimed at coders interested in understanding the building blocks of large language models (LLMs), how LLMs work, and how to

👏🏻 Congratulations to @AdwayKanhere, Software Engineer at the @UofMaryland, for winning the Best Poster Award at the @CVPR 2024 Workshop: Data Curation and Augmentation in Medical Imaging! 🌼 🚀 Workshop: https://t.co/bBsCUeKrgr 📖 Paper: https://t.co/Y6kOgKBKMe

🗓️ Flower Monthly is this Wednesday! 🤩 🔗 Link to join: https://t.co/YwBOvgGScF 📆 Jul 16:00 UTC 1️⃣ Dr. Siba Haidar (@SibaHaidar) Associate Professor from Learning Data Robotics (LDR) at @esiea_school 2️⃣ Adway Kanhere (@AdwayKanhere) Software Engineer from @UofMaryland

🚀 New Paper Alert! 🚀 "Radiomics workflow definition & challenges - German priority program 2177 consensus statement on clinically applied radiomics" 🌐Check out the paper here: https://t.co/XeAMBVvbwB 💡Project resources: https://t.co/D5P0Wd1at4