Global AI Infrastructure & Risk Landscape
Track frontier AI labs, data centers, and chip manufacturing across the globe
Important For: AI policymakers, safety researchers, institutional risk managers, and governance leaders monitoring frontier AI capabilities and risk assessments.
Recent AI Incidents
1,352
Incidents by Organization
Frontier Model Proximity to Thresholds
Current assessment of how close frontier models are to critical AI R&D acceleration thresholds across labs
AI Red Lines Tracker
Track how close frontier AI models are to critical risk thresholds using official system cards and preparedness frameworks. Compare risk assessments across OpenAI, Anthropic, Google DeepMind, and xAI, monitor training compute and infrastructure, and stay informed on regulatory compliance.
Risk Categories
- • Biological and Chemical Threats
- • Cybersecurity
- • Persuasion and Manipulation
- • AI Self-Improvement
Risk Levels
- • Low - Minimal capability
- • Medium - Moderate capability with mitigations
- • High - Significant capability requiring controls
- • Critical - Extreme capability requiring intervention
Frontier Labs Risk Analysis
Compare risk assessments across OpenAI, Anthropic, and Google DeepMind using their respective frameworks and evaluation methodologies
Compute Resources & Infrastructure
Track training compute, data center expansion, market concentration, and AI chip shipments across frontier labs
Explore how OpenAI, Anthropic, and Google DeepMind define and measure AI capabilities for accelerated research cycles. Compare red line definitions, METR benchmark results, and areas of convergence and divergence in frontier AI safety approaches.
Red Line Definitions
Lab-specific threshold definitions for R&D acceleration
METR Benchmarks
Autonomy evaluation frameworks measuring research capability
Convergence Analysis
Areas of alignment and divergence across labs