Epoch AI
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AI research institute shaping AI trajectory and governance
Epoch AI Product Information
Epoch AI Publications & Commentary is a research-focused platform that analyzes and visualizes key trends in artificial intelligence. It aggregates essential publications, data resources, and interactive benchmarks to help researchers, policymakers, and industry stakeholders understand the trajectory of AI development, scaling dynamics, and governance considerations. The site emphasizes transparency by linking to datasets, benchmarks, and data-driven insights from the Epoch AI team and collaborators.
What you can find on Epoch AI
- Essential publications and resources (e.g., Notable AI Models, AI Benchmarking Hub, Frontiers in AI, and data-backed analyses).
- Data and resources pages that host datasets, benchmarks, and training compute statistics.
- Project pages such as FrontierMath and GATE, plus tools for distributed training and model scaling analysis.
- AI Trends & Statistics that curate curated metrics like training compute growth, compute power, and hardware trends.
- Data Insights and visualizations that illustrate the dynamics of model scaling, hardware capacity, and energy considerations.
- Publications & Commentary with regularly updated gradient updates, After Hours briefs, and expert opinions.
- Information about the team, funding, collaborations, and career opportunities.
How to Use Epoch AI
- Explore Publications & Commentary to get a sense of the latest analyses and opinions from researchers and policy experts.
- Browse Data & Resources for datasets, benchmark results, and training compute metrics related to notable models.
- Dive into Projects like FrontierMath and GATE to understand trajectories of AI and automation, as well as modeling approaches.
- Consult AI Trends & Statistics to view curated numbers on training compute growth, data usage, and hardware capacity.
- Check Publications & Commentary sections for updates, interviews, and policy-relevant insights.
Data & Resources (Key Sections)
- Notable AI Models Data | Updated Apr. 08, 2025
- AI Benchmarking Hub | Data on model performance across challenging tasks
- FrontierMath Project
- GATE Project: Modeling the Trajectory of AI and Automation
- Training Compute & Costs statistics
- Training compute growth, data availability, and hardware insights
Safety and Responsible Use
- Information is meant for research, policy discussion, and education. Users should align interpretations with the original sources and consider governance and ethical implications when applying insights.
Core Features
- Central hub for AI publications and commentary with frequent updates
- Notable AI Models and Benchmarking data to track progress
- Data & Resources repositories for benchmarks, compute, and datasets
- Interactive project pages (FrontierMath, GATE, Distributed Training) for deeper analysis
- AI Trends & Statistics with quantified growth rates and confidence intervals
- Researcher-facing tools and resources, with clear attribution and publication dates
What’s Included in the Data & Resources
- Notable AI Models Data | Notable AI Models Report | Aug. 20, 2024
- AI Benchmarking Hub: performance data across leading models
- FrontierMath Project: modeling AI trajectories and automation
- GATE: Modeling the Trajectory of AI and Automation
- Training compute & capacity insights (growth rates, costs, and hardware trends)
- Curated insights on data usage, training efficiency, and scaling dynamics
- Public-facing research summaries and policy-relevant analyses
Annotations and Visualizations
Epoch AI’s pages include a variety of visualizations such as trend lines for training compute growth, dashboards showing model scale over time, and charts linking model families to compute and data usage. These visuals help contextualize debates about AI scaling, compute concentration, and governance implications.
Final Note
Epoch AI positions itself as a resource for society-centered AI governance and policy discussions, offering rigorous, data-backed perspectives on how AI systems scale, the energy and compute demands involved, and the implications for researchers, industry, and regulators.