Ingmar Posner

@IngmarPosner

Applied Machine Learner, Roboticist, Professor at University of Oxford.

Joined February 2017

285 Following 2.1K Followers 177 Posts

Latest posts 5

Really enjoyed talking robotics and where AI goes next with the @BBC AI Decoded team.

A wide ranging discussion from the World Humanoid Robot Games to world models, robot manipulation, uncertainty, data, deployment, and quite a bit in between.

And still so much more to say.

Ingmar Posner @IngmarPosner Jul 16

Introducing: Mechanistic World Models.

Scientific discovery is not just prediction. It requires uncovering the mechanisms generating what we observe. A capability current ML lacks.

With @AnsonISL and @bschoelkopf.
@a2i_oxford, @oxengsci and @MPI_IS.
arxiv.org/abs/2607.12474

Ingmar Posner @IngmarPosner Jun 30

Delighted to be back at the @royalsociety #SummerScience Exhibition with a team of humans and robots, showcasing research from our @EPSRC Programme Grant on Embodied Intelligence and across the wider @OxfordRobotics Institute.

If you're in London this week, come and say hello!

Ingmar Posner @IngmarPosner Jan 9

Are world models the missing piece for truly dexterous tactile robots? 🤖

Great to join the @ARIA_research programme meeting on robot dexterity to discuss how predictive models perform in contact-rich settings.

#WorldModels #Robotics #ARIA @a2i_oxford @oxfordrobots

Ingmar Posner @IngmarPosner Jan 7

A recurring theme in our recent work (e.g. SPARTAN): predictive world models become more interpretable when they help identify which parts of the input stream actually influence behaviour.

Learning what matters, not just what happens, is central.
arxiv.org/pdf/2411.06890

Anson Lei @AnsonISL Dec 6, 2024

Very excited to share our new work - SPARTAN: A Sparse Transformer Learning Local Causation.

We develop a Transformer world model that learns local causal dependencies between entities, leading to improved adaptation efficiency and robustness with accurate prediction.

🧵

View quoted post on X