After a year of team work, we're thrilled to introduce Depth Anything 3 (DA3)! 🚀 Aiming for human-like spatial perception, DA3 extends monocular depth estimation to any-view scenarios, including single images, multi-view images, and video. In pursuit of minimal modeling, DA3 reveals two key insights: 💎 A plain transformer (e.g., vanilla DINO) is enough. No specialized architecture. ✨ A single depth-ray representation is enough. No complex 3D tasks. Three series of models have been released: the main DA3 series, a monocular metric estimation series, and a monocular depth estimation series. The core team members, aside from me: @HaotongLin, Sili Chen, Jun Hao Liew, @donydchen. 👇(1/n) #DepthAnything3

Our Gemini 2.5 tech report ✨ is finally out on arXiv -- grateful for the collaboration with brilliant colleagues! arxiv.org/pdf/2507.06261

Great overview on the parallelism techniques needed for LLM training/inference from the new CS336 class at Stanford (Tatsunori Hashimoto & Percy Liang): youtube.com/watch?v=l1RJcDjz…. Info-dense and doesn't shy away from the technical details!

More than 5x growth in paid trips from this time last year — each ride contributing to safer streets and more accessible mobility for all. Here’s to millions more!

Thrilled to share that the amazing work of @stan188249301 (@maxjiang93's and I's intern at Waymo Research last summer) is accepted to CVPR 2025! SceneDiffuser fulfills a vision we've had in mind for several years, and we weren't sure if it was even possible. More details soon!

🥁Introducing Gemini 2.5, our most intelligent model with impressive capabilities in advanced reasoning and coding. Now integrating thinking capabilities, 2.5 Pro Experimental is our most performant Gemini model yet. It’s #1 on @lmarena_ai leaderboard. 🥇