Pedro A. Ortega

AGI and Cybernetics Researcher

Founder of the AGI startup DAIOS. Previously I was VP of Research at Kosen Labs and the lead of the Safety Analysis Team at DeepMind. My research focuses on artificial general intelligence and the formal principles of intelligence, covering aspects such as learning, planning and decision making in both machines and biological organisms. My approach lies at the intersection between machine learning, computational neuroscience, theoretical economics, and physics.

Specifically, I made pioneering contributions to very large-scale planning, causality in reinforcement learning, the connection between meta-learning and Bayesian statistics, and technical AI safety.

Most of my work centers on information-theoretic and statistical mechanical approaches to learning and control, leading to contributions in bounded rationality models and recasting adaptive control as a causal inference problem. I have also worked on causal induction, and on game- and decision-theoretic models in computational neuroscience.

To get a sense of my work, please refer to:

• my PhD thesis on bounded rationality and Bayesian control,
• my paper on Thompson sampling as Bayesian causal inference,
• my paper on bounded rationality through thermodynamic principles,
• or my publications.

I was part of the former Tuebingen group on Sensorimotor Learning and Decision Making, where some of the now widespread ideas on Thompson sampling, causality, and thermodynamic methods for reinforcement learning have originated.

• 11 September 2024: Talk at the Gatsby Computational Neuroscience Unit, UCL, London.
• 4 June 2024: Public release of MindScript, an experimental programming language. Browse the repo on GitHub.
• 2 April 2024: Panel speaker at the [Warwick AI Safety Summit 2024, 17 February 2024.
• 14 November 2023: Talk on information-theoretic bounded rationality at the Oxford AI Society.
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