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Jared Kaplan

Thought Leader

Jared Kaplan is the Chief Science Officer and Co-founder of Anthropic, the AI safety company behind the Claude family of large language models. He is best known for co-authoring the landmark neural scaling laws papers while at OpenAI, which demonstrated that the performance of large language models follows predictable power-law relationships with model size, dataset size, and compute — findings that have since become foundational to how AI labs plan and resource their model development efforts. These scaling laws gave the industry a scientific framework for understanding when and how to invest in larger models, influencing billions of dollars in AI infrastructure decisions. Before co-founding Anthropic in 2021, Kaplan was a researcher at OpenAI, where he contributed to some of the most influential empirical work in modern AI. His academic background is in theoretical physics — he holds a PhD in physics and spent time as a faculty member at Johns Hopkins University — and he brought a physicist's rigor for identifying universal laws to the study of deep learning systems. This cross-disciplinary perspective has distinguished his approach to AI research, grounding ambitious empirical claims in careful quantitative analysis. At Anthropic, Kaplan leads the scientific research agenda, helping to shape the company's approach to building safe, steerable, and interpretable AI systems. Anthropic's Claude models have become significant players in the enterprise AI and API ecosystem, with broad adoption across industries including media, marketing technology, and data analytics. While Kaplan's work is rooted in foundational AI research, the large language model capabilities he has helped pioneer are increasingly central to advertising automation, content generation, audience intelligence, and AI-driven campaign optimization across the industry.

Last updated Oct 14, 2026 by the ATDb Editorial Team

Role
Chief Science Officer & Co-founder
Company
Anthropic
Based
San Francisco, California, United States
Connections
2

AI-drafted from public sources7 sources cited

Years in industry
10 years

Bio

Jared Kaplan is the Chief Science Officer and Co-founder of Anthropic, the AI safety company behind the Claude family of large language models. He is best known for co-authoring the landmark neural scaling laws papers while at OpenAI, which demonstrated that the performance of large language models follows predictable power-law relationships with model size, dataset size, and compute — findings that have since become foundational to how AI labs plan and resource their model development efforts. These scaling laws gave the industry a scientific framework for understanding when and how to invest in larger models, influencing billions of dollars in AI infrastructure decisions. Before co-founding Anthropic in 2021, Kaplan was a researcher at OpenAI, where he contributed to some of the most influential empirical work in modern AI. His academic background is in theoretical physics — he holds a PhD in physics and spent time as a faculty member at Johns Hopkins University — and he brought a physicist's rigor for identifying universal laws to the study of deep learning systems. This cross-disciplinary perspective has distinguished his approach to AI research, grounding ambitious empirical claims in careful quantitative analysis. At Anthropic, Kaplan leads the scientific research agenda, helping to shape the company's approach to building safe, steerable, and interpretable AI systems. Anthropic's Claude models have become significant players in the enterprise AI and API ecosystem, with broad adoption across industries including media, marketing technology, and data analytics. While Kaplan's work is rooted in foundational AI research, the large language model capabilities he has helped pioneer are increasingly central to advertising automation, content generation, audience intelligence, and AI-driven campaign optimization across the industry.

Career

Roles with a cited source. All linked roles are in the Roles tab.

Expertise & education

Expertise

Large Language ModelsNeural Scaling LawsAI SafetyFoundation ModelsGenerative AIAI for Content and AutomationDeep Learning ResearchAI Infrastructure and Compute Strategy

Education

  • PhD, Physics, University of California, Berkeley
  • BA, Physics, University of Chicago

Speaking topics

Neural scaling laws and the future of large language modelsAI safety and alignment researchThe science of foundation model developmentCompute, data, and model scaling trade-offsGenerative AI applications across industries

Recognition

Notable achievements

  • Co-authored 'Scaling Laws for Neural Language Models' (2020), one of the most cited and influential papers in modern AI research
  • Co-founded Anthropic in 2021, which has grown into one of the leading AI safety and frontier model companies globally
  • Helped establish the scientific basis for compute-optimal training, influencing model development strategies across the AI industry
  • Led scientific research underpinning the Claude model family, widely adopted in enterprise, API, and marketing technology applications

Awards

Named to Forbes AI 50 (via Anthropic leadership recognition)

Publications

  • Scaling Laws for Neural Language Models (Kaplan et al., 2020, arXiv)
  • Training Compute-Optimal Large Language Models (Hoffmann et al., 2022 — influenced by Kaplan's scaling work)
  • Various physics publications from Johns Hopkins tenure
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