Understand contributions, disagreements, and consequences without creating a hall of fame.
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People, institutions, and ideas
How to read these profiles
Use a profile to understand a contribution in context: what changed, what remains disputed, which institutions mattered, and where the source record has limits.Choose by need
Profile · foundations
Turing helped establish what computation can mean mathematically and later asked how claims about machine intelligence might be made testable.
Profile · field formation
McCarthy helped give AI an institutional name and advanced programming and logical formalisms for representing and reasoning with knowledge.
Profile · symbolic and plural AI
Minsky helped establish major AI institutions and explored intelligence as an interaction among many specialized processes rather than one simple mechanism.
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Profile · deep learning
Hinton sustained and expanded neural-network research through periods of skepticism, helping develop methods and research communities central to modern deep learning.
Profile · learning and safety
Bengio helped build the conceptual foundations of deep learning and now concentrates much of his research and public work on advanced-AI safety.
Profile · vision and representation
LeCun helped turn convolutional neural networks into practical systems for visual and document recognition and now pursues architectures intended to learn predictive models of the world.
Profile · vision and data
Li led the creation of ImageNet with collaborators, helping make large, shared datasets and benchmarks central to progress in computer vision.
Profile · causality
Pearl developed influential graphical and mathematical tools for reasoning under uncertainty and for making causal assumptions explicit.
Profile · social robotics
Breazeal pioneered social robotics and human–robot interaction by studying how machines can use expressive cues and participate in structured social exchanges.
Profile · systems and science
Hassabis co-founded and leads DeepMind, an institution that has combined machine learning, search and large research teams in systems such as AlphaGo and AlphaFold.
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Profile · accountability
Gebru's research connects technical evidence about datasets and model performance with questions about who builds AI, who is affected and which institutions control research.
Profile · public evidence
Buolamwini combined empirical auditing, public communication and advocacy to make disparities in automated facial analysis visible and actionable.
