I'm excited to share our new work Diffusion as Shader (DaS), a versatile controllable video generation method for various tasks: object manipulation, camera control, mesh-to-video, and motion transfer. Project page: igl-hkust.github.io/das/ Github: github.com/IGL-HKUST/Diff…

Video, meet audio. 🎥🤝🔊 With Veo 3, our new state-of-the-art generative video model, you can add soundtracks to clips you make. Create talking characters, include sound effects, and more while developing videos in a range of cinematic styles. 🧵

Excited to introduce our new Veo 2 capabilities! Now with reference powered video generation (including style!), camera controls, outpainting, object add/removal & many more: deepmind.google/models/veo/#ca… Also presenting Flow, our new AI filmmaking tool. labs.google/flow

Do AI robots see the world like we do? I dove head first into latent space to uncover the attention maps that show how my robot sees and understands the world.

We move our eyes actively—driven by survival and efficiency—but we still don’t fully understand how. That makes supervised learning hard. In our new work, we explore how to train VLMs to reason visually using RL. ViGoRL offers a glimpse into how models like o3 might be trained.

[CVPR2025] Depth Any Camera: Zero-Shot Metric Depth Estimation from Any ... youtu.be/U1qGXx0QBwE?si… via YouTube

Log-linear attention — a new type of attention proposed by Massachusetts Institute of Technology (MIT) which is: - fast and efficient as linear attention - expressive as softmax It uses a small but growing number of memory slots that increases logarithmically with the sequence length. Here's how it works:

Excited to share that TokenVerse won Best Paper Award at SIGGRAPH 2025! 🎉 TokenVerse enables personalization of complex visual concepts, from objects and materials to poses and lighting, each can be extracted from a single image and be recomposed into a coherent result. 👇

The neural network objective function is a very complicated objective function. It's very non convex, and there are no mathematical guarantees whatsoever about its success. And so if you were to speak to somebody who studies optimization from a theoretical point of view, they

TRI's latest Large Behavior Model (LBM) paper landed on arxiv last night! Check out our project website: toyotaresearchinstitute.github.io/lbm1/ One of our main goals for this paper was to put out a very careful and thorough study on the topic to help people understand the state of the

AI that truly understands the physical world should not be limited by robot type or tasks. We tackle robotics in its full generality Skild AI. The goal is to build a continually improving, omni-bodied brain that can control any hardware for any task.

We’ve all seen humanoid robots doing backflips and dance routines for years. But if you ask them to climb a few stairs in the real world, they stumble! We took our robot on a walk around town to environments that it hadn’t seen before. Here’s how it works🧵⬇️

Rugged by design. Elevated by nature. The #LucidGravityX concept redefines what a trail-ready adventure vehicle could be. Read more about our new bold concept: bit.ly/46Yu886

Ever wish a robot could just move to any goal in any environment—avoiding all collisions and reacting in real time? 🚀Excited to share our #CoRL2025 paper, Deep Reactive Policy (DRP), a learning-based motion planner that navigates complex scenes with moving obstacles—directly

A robotic ballet! 🩰 Coordinating multiple robot arms on a busy factory floor is notoriously complex. Each arm needs to move without colliding with its neighbors or the surrounding equipment, and today that planning is still mostly done by hand, a process that takes specialists

We built a robot brain that nothing can stop. Shattered limbs? Jammed motors? If the bot can move, the Brain will move it— even if it’s an entirely new robot body. Meet the omni-bodied Skild Brain:

😠💢😵‍💫Tired of endless data collection & fine-tuning every time you try out VLA? Meet RDT2, the first foundation model that zero-shot deploys on any robot arms with unseen scenes, objects & instructions. No collection. No tuning. Just plug and play🚀 Witness a clear sign of

🔉 Introducing SAM Audio, the first unified model that isolates any sound from complex audio mixtures using text, visual, or span prompts. We’re sharing SAM Audio with the community, along with a perception encoder model, benchmarks and research papers, to empower others to

Humans learn by watching. Robots should too.

Announcing Series C We’ve raised $1.4B, valuing the company at over $14B With this capital, we will accelerate our mission to build omni-bodied intelligence 🚀 skild.ai/blogs/series-c