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About

Armin W. Thomas is a leading researcher at the intersection of artificial intelligence, cognitive science, and computational neuroscience. His work explores how large-scale AI models—particularly foundation models like GPT-3 and BERT—can inform our understanding of human cognition, and conversely, how insights from the brain can guide the development of more robust and interpretable AI systems. Thomas is best known for his pivotal contributions to the landmark report "On the Opportunities and Risks of Foundation Models" (2021), which has garnered over 2,100 citations and helped define the modern AI paradigm. This work critically examined the societal and technical implications of models trained on broad data at scale, highlighting both their transformative potential and their inherent risks. Beyond this, Thomas has made significant strides in using neural network representations to model human decision-making and perception, bridging the gap between machine learning and cognitive psychology. His research is widely cited and has influenced discussions on AI safety, alignment, and the responsible deployment of generative models. A prolific scholar, Thomas continues to shape the dialogue on how we build, understand, and govern increasingly powerful AI systems.