Epoch AI Introduction
Epoch AI is a multidisciplinary research institute investigating key trends and questions that will shape the trajectory and governance of artificial intelligence.
View MoreWhat is Epoch AI
Epoch AI is a research institute dedicated to studying the development and impact of artificial intelligence. Founded with the mission of understanding AI's trajectory for the benefit of society, Epoch AI produces papers, reports, datasets, and visualizations on the drivers, trajectory, and consequences of AI development and deployment. The institute takes an empirical, data-driven approach to analyzing trends in machine learning and forecasting the future of AI capabilities.
How does Epoch AI work?
Epoch AI conducts its research through several key activities. It maintains comprehensive databases of notable machine learning models and their characteristics, allowing for analysis of historical trends. The institute produces reports and academic papers investigating topics like algorithmic progress, compute usage in AI, and potential bottlenecks to AI development. Epoch AI also creates interactive data visualizations and dashboards to make its findings accessible. Additionally, the institute collaborates with other organizations, contributes to policy discussions, and engages in public outreach to disseminate its research.
Benefits of Epoch AI
Epoch AI's work provides valuable insights for researchers, policymakers, and the public seeking to understand the rapidly evolving field of AI. Its rigorous, data-driven approach helps ground discussions about AI progress in empirical evidence rather than speculation. The institute's comprehensive databases and analyses serve as key resources for tracking trends in AI capabilities. By investigating important questions about AI's trajectory, Epoch AI aims to inform decision-making and governance efforts to ensure AI is developed in ways that benefit society.
Epoch AI Monthly Traffic Trends
Epoch AI saw a 18.5% increase in visits, reaching 92,883. This growth can be attributed to the expanded database that now includes biological sequence models, which are trained on protein, DNA, or RNA sequences, and the significant increase in compute usage for these models. The addition of notable models like xTrimoPGLM-100B likely attracted more researchers and developers.
View history traffic
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