Adam Jelley

Adam Jelley

Research / Co-Founder

General Intuition

Hello!

I’m a Member of Technical Staff / Co-Founder at General Intuition. We work on foundation models that require deep spatial and temporal reasoning. Our models are built on the billions of hours of gameplay recorded with Medal, with applications to the video game industry and beyond.

Before starting General Intuition, I was a PhD student working on efficient reinforcement learning approaches and world models in the Bayesian and Neural Systems group at the University of Edinburgh, lucky to be supervised by Professor Amos Storkey in the School of Informatics as well as Sam Devlin from the Game Intelligence Team at Microsoft Research Cambridge. I was supported by a Microsoft Research Scholarship.

Interests
  • Reinforcement Learning
  • Imitation Learning
  • World Models
  • RL from Human Feedback
  • Self-Supervised Learning
  • AI for Science
Education
  • PhD in Generating Environments and Pre-Training Agents for Efficient Reinforcement Learning, 2025

    University of Edinburgh

  • MSci in Theoretical Physics, 2016

    University of Cambridge

  • MA in Natural Sciences - Physics, 2015

    University of Cambridge

Selected Publications

Experience

 
 
 
 
 
General Intuition
Research / Co-Founder
Apr 2025 – Present
Research into foundation models that require deep spatial and temporal reasoning.
 
 
 
 
 
University of Edinburgh
PhD Candidate
May 2021 – Jul 2025 Edinburgh

PhD Candidate in Efficient Reinforcement Learning and World Models.

Thesis: Generating Environments and Pre-Training Agents for Efficient Reinforcement Learning

 
 
 
 
 
Microsoft Research Cambridge
Research Scientist Intern
Jun 2023 – Sep 2023 Cambridge
Developed a pipeline for aligning agents with preferences on the Xbox game Bleeding Edge, for research into capabilities and limitations of Reinforcement Learning from Human Feedback (RLHF) in this domain.
 
 
 
 
 
Dataiku
Lead Data Scientist
Jul 2020 – Apr 2021 London
Led the UK and Northern Europe region’s data science team of 6 data scientists to deliver data science projects and coaching.
 
 
 
 
 
Dataiku
Data Scientist
Apr 2019 – Jul 2020 London
Delivered client-facing and internal data science projects and coaching.
 
 
 
 
 
UCL
Research Student
Sep 2018 – Mar 2019 London
Initial research training at Centre for Doctoral Training in Data Intensive Science.
 
 
 
 
 
Analysed and modelled trials of new initiatives to predict their wider impact. Presented recommendations back to clients to inform decisions.
 
 
 
 
 
University of Cambridge
Undergraduate Student
Oct 2012 – Jun 2016 Cambridge
Part III Theoretical Physics MSci and Natural Sciences Tripos Undergraduate Student.