Dario Amodei
CEO And Co-Founder at Anthropic
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolDario Amodei is a veteran AI researcher and entrepreneur with nine years in industry leadership, currently co-founding and serving as CEO of Anthropic to build steerable, interpretable, and robust large-scale AI systems focused on long-term alignment. Previously he shaped strategy and led research teams at OpenAI, where he was instrumental in developing GPT-2 and GPT-3 and directed long-term safety and interpretability work. His background spans deep learning research at Google Brain and Baidu—contributing key advances in speech recognition and neural architectures—and a PhD in biophysics from Princeton grounded in computational neuroscience. Known for bridging rigorous research with product impact, he often pairs novel theory with practical engineering (e.g., decoder and training speedups at Baidu and widely adopted proteomics algorithms). Based in San Francisco, he combines a rare mix of scientific depth, systems-level thinking, and operational experience scaling safety-focused AI teams.
9 years of coding experience
8 years of employment as a software developer
BS Physics, BS Physics at Stanford UniversityCalifornia Institute of TechnologyPhD (Bio)physics, PhD (Bio)physics at Princeton University
Github Skills (7)
gymnasium10
q-learning10
reinforcement-learning10
universe9
machine-learning9
deep-learning9
artificial-intelligence8
Programming languages (1)
Github contributions (3)
openai/universe
Jan 2017 - Jul 2017
Universe: a software platform for measuring and training an AI's general intelligence across the world's supply of games, websites and other applications.
Contributions:2 commits, 1 push, 1 branch in 5 months
universegamesmachine-learningtrainingmeasuring
openai/gym
Oct 2016 - Jan 2017
A toolkit for developing and comparing reinforcement learning algorithms.
Contributions:4 commits, 1 PR, 3 pushes in 3 months
comparingreinforcement-learning-algorithmsdevelopingdeep-learningreinforcement-learning
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