Person
Dario Amodei
Dario Amodei is the co-founder and CEO of Anthropic. He previously worked at OpenAI, where he was Vice President of Research and co-authored the GPT-2 paper and led the research for GPT-3.
Born 1983
AffiliationsOpenAIAnthropicStanford UniversityGoogle BrainAll 5
Overview
Dario Amodei is the co-founder and chief executive of Anthropic, the company behind the Claude models.[1][4] Before founding Anthropic he worked at OpenAI, where he became Vice President of Research.[4] Anthropic was founded in 2021, after his OpenAI years.
Education and early career
Amodei attended Caltech and then earned a bachelor’s degree in physics from Stanford. He received a PhD in biophysics from Princeton, where he held a Hertz Foundation Fellowship in 2007 and won the Hertz Thesis Prize in 2011. He was also a postdoctoral scholar at Stanford University School of Medicine.[1]
Baidu is a Chinese internet company, and Google Brain is Google’s AI research team.[1]
Key contributions
In June 2017 Amodei co-authored “Deep reinforcement learning from human preferences” with Paul Christiano, Jan Leike, Tom B. Brown, Miljan Martic and Shane Legg.[2] The method trains an AI system using human judgments. People compare pairs of behaviours, a model learns to predict those preferences, and reinforcement learning then adjusts the system against that learned signal. This general approach later became one of the main ways to steer language models toward helpful behaviour. The idea is that people can often express preferences by comparing two outputs more easily than by writing a precise score, so the system learns from which output people prefer.
At OpenAI he worked on GPT-2, on which he is a co-author of the paper, on “Scaling Laws for Neural Language Models,” and on GPT-3.[1] The GPT-3 paper states that “Dario Amodei designed and led the research.”[3] GPT-3 is a large language model, and its paper examined what such a model can do when it is given only a few examples of a task in its input.[3]
In October 2024 he published the essay “Machines of Loving Grace: How AI Could Transform the World for the Better.” It describes a possible “country of geniuses in a datacenter” and a “compressed 21st century” of scientific progress.[5]
Positions
Amodei left OpenAI at the end of 2020. OpenAI’s December 2020 organisational update thanked him for his contributions over four and a half years.[4]
In 2021 he co-founded Anthropic with Daniela Amodei and other former senior OpenAI members, and he has been its CEO since.[1]
Impact and recognition
In 2025 Amodei was named to the TIME100 AI list and to TIME’s list of the 100 most influential people. He was also included in TIME’s Person of the Year coverage of the “Architects of AI.”[6] The essay mentioned above is one of his main written statements about how AI could affect science and the wider economy.[5] It is an essay rather than a technical paper, so its claims are best read as his stated views rather than as established results.
CapabilitiesLarge language models
TechniquesFoundation models
Governance & standardsSafety & governance
HistoryResearch history
Career timeline
12-
1746
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Princeton University
Worked at
Princeton University, chartered in 1746 as the College of New Jersey, is where Turing, McCarthy and Minsky took their doctorates and where Fei-Fei Li began ImageNet; seventeen Turing Award laureates have been affiliated with it.
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Princeton University
Worked at
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1885
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Stanford University
Worked at
Stanford University is a private research university in California, home to the Stanford AI Lab (SAIL) and the Institute for Human-Centered AI, which publishes the AI Index.
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Stanford University
Worked at
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2015
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Google Brain
Worked at 2015–2016
Google Brain was a deep-learning research team started inside Google's X in 2011. Its cat-recognition experiment, TensorFlow, sequence-to-sequence models and the Transformer made it central to modern AI; it merged into Google DeepMind in 2023.
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Google Brain
Worked at 2015–2016
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2016
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OpenAI
Worked at 2016–2020
OpenAI is a San Francisco AI research and deployment company founded in 2015 as a nonprofit. It makes the GPT model family and ChatGPT and filed confidentially for an IPO in June 2026.
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OpenAI
Worked at 2016–2020
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2017
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Deep reinforcement learning from human preferences
Contributed to
A 2017 paper showing that an AI agent can learn a task from short human comparisons instead of a hand-written reward. The method, reinforcement learning from human feedback, later became central to training chat assistants.
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Deep reinforcement learning from human preferences
Contributed to
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2019
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Language Models are Unsupervised Multitask Learners (GPT-2)
Contributed to
OpenAI's 2019 paper on GPT-2, a 1.5-billion-parameter Transformer trained on web text. It showed that a model trained only to predict the next word could perform several tasks when prompted, and its staged release sparked public debate.
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GPT-2
Contributed to
GPT-2 is a large language model that OpenAI announced in February 2019. Its largest version has 1.5 billion parameters. OpenAI first withheld the full model, then released it in stages through November 2019.
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Language Models are Unsupervised Multitask Learners (GPT-2)
Contributed to
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2020
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Scaling Laws for Neural Language Models
Contributed to
A 2020 paper finding that language model loss falls predictably, as a power law, with model size, data and compute. It gave labs a quantitative reason to build much larger models and shaped the scale-up that followed.
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GPT-3
Contributed to
GPT-3 is an autoregressive language model with 175 billion parameters, described in a May 2020 paper. It could perform new tasks from a few examples in the prompt, without any gradient updates, and it was first offered through OpenAI's API.
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Language Models are Few-Shot Learners (GPT-3)
Contributed to
The GPT-3 paper showed that a language model with 175 billion parameters could perform many tasks from a few examples in its prompt, with no fine-tuning, and that this ability grew with model size.
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Scaling Laws for Neural Language Models
Contributed to
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2021
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Anthropic
Founded、Worked at 2021–
Anthropic is an AI safety and research company founded in January 2021 by former OpenAI employees. It develops the Claude models and products, and its Responsible Scaling Policy sets out safety levels for its models.
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Anthropic
Founded、Worked at 2021–
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2022
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Constitutional AI: Harmlessness from AI Feedback
Contributed to
Constitutional AI, a 2022 paper from Anthropic, proposes training a harmless AI assistant with AI-generated feedback guided by a written set of principles, instead of human labels of harmful outputs.
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Constitutional AI: Harmlessness from AI Feedback
Contributed to
Worked at5
Founded1
20261
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PolicyIndia hosts the AI Impact Summit 2026
India hosted the AI Impact Summit 2026 in New Delhi from 16 to 21 February 2026, the first edition of the global AI summit series held in the Global South. A declaration was endorsed by 92 countries and organisations, and 13 model providers signed frontier AI commitments.
20232
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FundingAmazon agrees to invest up to $4 billion in Anthropic
On 25 September 2023 Amazon agreed to invest up to $4 billion in Anthropic and take a minority stake. AWS became Anthropic's primary cloud provider and gave Anthropic access to Trainium and Inferentia chips.
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PolicyAI scientists sign a one-sentence statement on extinction risk
On 30 May 2023 the Center for AI Safety published a one-sentence statement arguing that mitigating the risk of extinction from AI should be a global priority, and leading researchers and lab executives signed it.
20211
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MilestoneAnthropic is founded
Anthropic, an AI company, was incorporated in January 2021 by former employees of OpenAI and set up as a public benefit corporation. Dario Amodei became its chief executive and Daniela Amodei its president.
20201
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PaperOpenAI publishes the GPT-3 paper
In May 2020 OpenAI published the GPT-3 paper, describing a 175-billion-parameter language model that performs new tasks from a few examples given in its text input, without additional training.
20191
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ReleaseOpenAI announces GPT-2 and holds back the full model
On 14 February 2019 OpenAI announced GPT-2, a 1.5-billion-parameter Transformer that performed several language tasks without task-specific training. It did not release the full model at first, instead releasing it in stages.
Notes and sources
- Dario Amodeihttps://en.wikipedia.org/wiki/Dario_Amodei
- Deep reinforcement learning from human preferenceshttps://arxiv.org/abs/1706.03741
- Language Models are Few-Shot Learnershttps://arxiv.org/abs/2005.14165
- Dario Amodei leaves OpenAI (linkpost of OpenAI's organizational update)https://www.greaterwrong.com/posts/7r8KjgqeHaYDzJvzF/dario-amodei-leaves-openai
- Machines of Loving Gracehttps://www.darioamodei.com/essay/machines-of-loving-grace
- The 100 Most Influential People in AI 2025https://time.com/collections/time100-ai-2025/
Cite this page: Dario Amodei. TellWorld, https://www.tellworld.net/people/dario-amodei. Updated 2026-11-08