John Lambert

If so, we want to hear from you! To apply, please follow these two steps: 1️⃣ Fill out the form below to personally express your interest to me: docs.google.com/forms/d/e/1FAI… 2️⃣ Fill out the Google DeepMind "Student Researcher 2026" application form: google.com/about/careers/…

I am hiring a Student researcher at Google DeepMind for Winter/Spring or Summer of 2026! 🛠️ Interested in tool-use and reasoning for LLMs? 🚀 Up-to-date with frontier research? 🔬 Love to understand code & algorithms from first principles? 📚 Currently studying for a BS/MS/PhD?

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

Thanks to the team: @maxjiang93 , @stan188249301 , @tanmingxing, @AnguelovDrago, @hongjjeonS, Sakshum Kulshrestha, Yijing Bai, Jing Luo. - SceneDiffuser++ Paper: arxiv.org/abs/2506.21976 - Watch our video: youtube.com/watch?v=J70R3w… - SceneDiffuser Paper: arxiv.org/abs/2412.12129

We propose a new task, CitySim, where given a city map and an AV software stack, the simulator can simulate the trip from point A -> B by populating the city around the AV and controlling all aspects of the scene (e.g., vehicles, pedestrians, traffic light states).

Can a single autonomous driving simulation world model jointly insert, delete, and control the behavior of all agents and traffic lights in a bird's-eye-view scene? For the first time, we show this is possible in SceneDiffuser++, our CVPR '25 paper, w/ 60+ second simulations.🧵

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=l1RJcD…. 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. 🥇

2️⃣ Fill out the Google DeepMind "Student Researcher 2025" application form: careers.google.com/jobs/results/?… *this role is onsite in Mountain View ☀️🌊

🚀 To apply, just follow these two steps [please **do not** contact me on X, I don't check the inbox often.] 1️⃣ Fill out the form below to personally express your interest to me and my team: docs.google.com/forms/d/e/1FAI…

I am hiring a Student Researcher at Google DeepMind for 2025! 👩🔬 Interested in improving multi-turn optimization and reasoning capabilities of LLMs? 🧑‍🎓 Currently studying for a Bachelor's/Master's/PhD? 🧑‍💻 Have solid engineering and research skills? 🌟We want to hear from you!

I am sincerely grateful to have been able to learn, grow, publish, mentor exceptional interns, and together build the Waymo Driver these past few years. Leaving behind exceptional colleagues is bittersweet, but I’m excited for what lies ahead. ✨✨

..especially in a city (SF) I myself have struggled to comfortably drive in for years. Waymo is delivering more than 150,000 rides *per week* with no driver -- truly the arc of progress is unstoppable. It has been my great privilege to work with so many brilliant colleagues here.

Career Update: After almost 3 years at Waymo Research, I've started a new chapter at Google DeepMind, joining the Gemini effort. After 7 years in the self-driving industry, it is been astonishing to see this technology evolve from a "moonshot" to a mundane everyday commute (1/n)