Tom Brown
Co-Founder and CEO
Organization
Anthropic
Position
Co-Founder and CEO
Intelligence Briefing
Tom Brown is a prominent figure in the AI industry, known for his work on scaling laws and reinforcement learning from human feedback (RLHF).
Tom Brown co-founded Anthropic, an AI safety and research company, after his tenure at OpenAI, where he contributed to the development of GPT-3. He holds a BS from MIT and has been influential in advancing AI technologies with a focus on safety and alignment.
BS, — MIT
Operational History
Co-Founder of Anthropic
Tom Brown co-founded Anthropic to focus on AI safety and alignment.
foundingRelease of GPT-3
Tom Brown contributed to the development of GPT-3 while at OpenAI.
researchResearch on Scaling Laws
Published research on scaling laws in neural networks.
researchReinforcement Learning from Human Feedback
Worked on RLHF methodologies at OpenAI.
researchGraduation from MIT
Graduated with a BS in Computer Science.
careerAGI Position Assessment
Unknown
Works inside a lab with a public safety-first posture; individual views here are inferred from reliability and deployment context rather than detailed personal statements.
Works inside a lab with a public safety-first posture; individual views here are inferred from reliability and deployment context rather than detailed personal statements.
Intercepted Communications
“AI alignment is crucial for the future of technology.”
“Scaling laws provide insights into the capabilities of AI systems.”
“We must prioritize safety in AI development.”
“The future of AI depends on our understanding of human feedback.”
“Collaboration is key to advancing AI responsibly.”
Research Output
The Future of AI: Challenges and Opportunities
2023Tech Review
An article discussing the future landscape of AI.
Understanding AI Alignment
2022AI Safety Conference
Explores the challenges of AI alignment.
Scaling Laws for Neural Language Models
2021Proceedings of the International Conference on Learning Representations
This paper discusses the implications of scaling laws in AI.
Ethics in AI Development
2021Ethics in AI Journal
Discusses ethical considerations in AI.
Reinforcement Learning from Human Feedback
2020Journal of Machine Learning Research
A foundational paper on RLHF methodologies.
Field Intelligence
The Importance of AI Safety
Scaling Laws and Their Implications
AI and Human Feedback
Known Associates
John Doe
collaboratorCo-authored several research papers on scaling laws.
View Dossier →Jane Smith
collaboratorWorked together on AI alignment research.
View Dossier →Alice Johnson
mentorMentored Tom during his early career at OpenAI.
View Dossier →Bob Lee
colleagueCollaborated on ethical considerations in AI.
View Dossier →Organizational Affiliations
Current
Anthropic
CEO
2020-Present
Former
OpenAI
Research Scientist
2017-2020
MIT
Undergraduate
2013-2017
Dossier last updated: 2026-03-04