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Marc Deisenroth

All AI minds
AI advancement report · generated from Marc Deisenroth's indicators

Marc Deisenroth — full AI read

Marc Deisenroth — DeepMind Chair of Machine Learning and AI, UCL, University College London (United Kingdom) — ranks #388/520 on the AI Advancement Index (65.1). Known for PILCO data-efficient model-based reinforcement learning, Gaussian processes for control, and the open textbook 'Mathematics for Machine Learning'.

Role
DeepMind Chair of Machine Learning and AI, UCL
Affiliation
University College London
Country
United Kingdom
Field
Reinforcement learning
Known for
PILCO data-efficient model-based reinforcement learning, Gaussian processes for control, and the open textbook 'Mathematics for Machine Learning'

Dimension read

DimensionValueStandingWhat a high vs low value means — and where Marc Deisenroth sits
AAI AI Advancement (AAI)65.1Developing · #385/520Low here — lower relative influence within this elite set.
▲ high: among the very top minds advancing AI  ·  ▼ low: lower relative influence within this elite set
Research influence Research influence72.0Moderate · #282/520Mid-pack. High would mean field-defining research contributions; low would mean limited direct research influence.
▲ high: field-defining research contributions  ·  ▼ low: limited direct research influence
Frontier role Frontier role50.0Developing · #450/520Low here — removed from frontier development.
▲ high: central to building today's frontier AI  ·  ▼ low: removed from frontier development
Thought leadership Thought leadership62.0Moderate · #313/520Mid-pack. High would mean shapes how the field and public think about AI; low would mean limited public/field influence.
▲ high: shapes how the field and public think about AI  ·  ▼ low: limited public/field influence
Field-building Field-building75.0Moderate · #178/520Mid-pack. High would mean builds the field — mentorship, institutions, tools, community; low would mean limited field-building footprint.
▲ high: builds the field — mentorship, institutions, tools, community  ·  ▼ low: limited field-building footprint
Momentum Momentum68.0Developing · #423/520Low here — less active at the current frontier.
▲ high: driving AI's advancement right now  ·  ▼ low: less active at the current frontier

Strengths

  • No standout dimension.

Risk factors

  • A significant, well-rounded contributor to AI's advancement.
These are model outputs and scenarios, not forecasts of actual outcomes. This platform measures access to, utilization of, and leverage from cognitive infrastructure — not intelligence. No causality or certainty is claimed.