Markus Wulfmeier

Other companies folded or dropped their divisions.

They've given up too early. Congratulations, not easy to accept you have been wrong and lucky I had no bets. Lots of learnings. Now to scaling the rest of robotics!

Waymo on X: "100 million real world, fully autonomous miles driven on public roads. That’s more than 200 trips to the Moon and back. Thank you riders. https://t.co/2EcE4Oqxnu" / X 100 million real world, fully autonomous miles driven on public roads. That’s more than 200 trips to the Moon and back. Thank you riders. https://t.co/2EcE4Oqxnu

#Robotics is hard, and so is #AutonomousDriving! Massive congratulations to my friends at #Waymo for proving me wrong!

x.com/Waymo/status...

There was a time a couple years back when I was getting skeptical about the scale of both technological and societal challenges for scaling autonomy....

Massive props to everyone organizing the #RSS2025 demo. I'm having a massive amount of fomo here.

Ayzaan Wahid on X: "We took a robot to RSS in LA running our new Gemini Robotics On-Device VLA model. People interacted with the model with new objects and instructions in a brand new environment and the results were amazing! https://t.co/0qZiGK2h0g" / X We took a robot to RSS in LA running our new Gemini Robotics On-Device VLA model. People interacted with the model with new objects and instructions in a brand new environment and the results were amazing! https://t.co/0qZiGK2h0g

Large language and vision models alone don't solve the whole #robotics problem.
But they surely have a massive impact on generalisation and robustness!

New scenes, new backgrounds, new objects, new people, new language and audio....

x.com/ayzwah/statu...

YouTube video by Google DeepMind Gemini Robotics on-device in simulation

Don't have a robot? Try our newest Gemini Robotics on-Device VLA in simulation!

Or become a trusted tester and tune and adapt the model yourself!

www.youtube.com/watch?v=nVMY...

Google DeepMind on X: "We’re bringing powerful AI directly onto robots with Gemini Robotics On-Device. 🤖 It’s our first vision-language-action model to help make robots faster, highly efficient, and adaptable to new tasks and environments - without needing a constant internet connection. 🧵 https://t.co/1Y21D3cF5t" / X We’re bringing powerful AI directly onto robots with Gemini Robotics On-Device. 🤖 It’s our first vision-language-action model to help make robots faster, highly efficient, and adaptable to new tasks and environments - without needing a constant internet connection. 🧵 https://t.co/1Y21D3cF5t

Thrilled to share something new: Fast, robust, and increasingly intelligent 🧠 🤖

Truly proud of our team and hoping you'll enjoy the model!

x.com/GoogleDeepMi...

The hardest problem with RL for robots is not RL!

Are there any great summary posts from @huggingface 's #LeRobot hackathon?

What works, what doesn't, how many robots broken ...? 🤖

Ever thought of joining DeepMind's RL team? We're recruiting for a research engineering role in London:
job-boards.greenhouse.io/deepmind/job...
Please spread the word!

Looking forward to talking about how much multiagentness do we need for multiagent RL for #robot soccer and other real world applications!

In half an hour at the #Robolethics workshop #ICRA2025 @GoogleDeepMind

If you blink, you've missed it! Demis Hassabis showing a glance into the future of robotics and vision language action models!

#GoogleDeepMind #GoogleIO #robotics

Looking forward to #ICRA2025 ! Find me (remotely) during the workshops and catch up on large-scale RL, IL, and multi agent learning with a side of vision language action models!

Agentic LLMs need to explore! The web is a non-stationary, highly partially unobservable 🏔️.

Thomas #GoogleDeepMind internship systematically investigates current challenges and the role of scale, RL, and chain-of-thought reasoning to overcome them.

arxiv.org/abs/2504.16078

Organisation: Andrey Kolobov, Alex Bewley, Hamidreza Kasaei, Anqi Li, Dhruv Shah, Ted Xiao, Georgia Chalvatzaki, Feras Dayoub, Rika Antonova, Roberto Calandra, Nur Shafiullah, Masha Itkina, Jonathan Tompson

With talks from Sandy Huang, Joseph Lim, Coline Devin, Davide Scaramuzza, Chris Paxton, David Hsu, Chelsea Finn

Google DeepMind KAIST Universität Zürich Hello Robot Inc National University of Singapore Physical Intelligence Stanford University Microsoft Research

Visiting #ICLR2025? Join for the 7th iteration of the #RobotLearning workshop 🤖🧠 (rather than the usual at NeurIPS)! Rather than human-like form, how far are we from human-level abilities?

Join the fun in person (while I will be cheering the team from London)!

www.robot-learning.ml/2025/

Thanks to OpenAI for sharing these discussions on on challenges with GPT4.5 and a bit more 'openness' 😉

YouTube video by OpenAI Pre-Training GPT-4.5

As data becomes more valuable than compute, being able to invest compute to extract more information from the same amount of data is invaluable!

youtu.be/6nJZopACRuQ?...

Apprenticeship learning, inverse RL, ... are becoming really interesting again! proceedings.neurips.cc/paper_files/...

Google PhD fellowship program The Google PhD Fellowship Program recognizes outstanding graduate students doing exceptional work in computer science, related disciplines, or promising research areas.

Deadline May 15th! The Google #PhDFellowship applications are open! Many fantastic friends are mentoring this year.

Check out research areas and details here research.google/programs-and...

Needing #selfdriving, #reinforcementlearning, and #llm reviewers for #IROS2025 ! Please reach out.

My group @FLAIR_Ox is recruiting a postdoc and looking for someone who can get started by the end of April. Deadline to apply is in one week (!), 19th of March at noon, so please help spread the word: my.corehr.com/pls/uoxrecru...

Please share mail, papercept pin, expertise and google scholar when reaching out.

#IROS2025 reviews are coming up! Please let me know if you're interested in reviewing.

Thorough and constructive reviews are a backbone for scientific progress, please reach out!

#robotics #robotlearning #reinforcementlearning #transferlearning #imitationlearning

Google DeepMind on LinkedIn: Gemini Robotics brings AI into the physical world Meet Gemini Robotics: our latest AI models designed for a new generation of helpful robots. 🤖 ⚡ Gemini Robotics is our most advanced vision-language-action…

'Gemini, meet robot. Robot, meet Gemini. You're going to have a lot of fun together. '

Truly impressive work led by our friends and colleagues at @GoogleDeepMind Robotics!

Check out how far we get with just little data!

www.linkedin.com/posts/google...

#artificialintelligence #multiagentsystems #reinforcementlearning… | Prorok Lab 🚀 What an inspiring session! 🚀 A huge thank you to Markus Wulfmeier from Google DeepMind for delivering an outstanding lecture 'Learning to Interact in…

Thank you Amanda Prorok for the invitation. it was a pleasure to discuss the degree 'multi-agent ness' across our applications in language, robotics, and navigation @GoogleDeepMind!

Looking forward to many further fruitful conversations.
www.linkedin.com/posts/prorok...

'" Eventually, they say, robots imbued with A.I. will learn from trial and error in the real world, as humans and animals do.

“Learning to control a body through reinforcement learning — that is a very natural thing,” Dr. Barto said."'

Turing Award Goes to A.I. Pioneers Andrew Barto and Richard Sutton Andrew Barto and Richard Sutton developed reinforcement learning, a technique vital to chatbots like ChatGPT.

#ReinforcementLearning (Barto&Sutton) wins the Turing! Wonderful recognition for two personal heroes of mine as well as for the whole field!

www.nytimes.com/2025/03/05/t...

1. Humans are incredibly flexible and able to fill the ability gaps in any systems faster than research will.

2. We want to be creative, solve problems, etc. We want assistants, not replacements.

Two reasons why we're moving towards shared/augmented intelligence.

1. It is much easier.
2. It is actually what we want.

👇

The best AND worst thing about teleoperating robots (and BC): it (approx) linearly scales ability with investment.