Monitoring and tracking artificial intelligence development and risk assessment in real-time.

Skynet Chance (-0.03%): Investment in rigorous AI evaluation and benchmarking infrastructure strengthens our ability to assess AI capabilities and limitations, contributing marginally to safer AI development. The focus on third-party, non-company-specific benchmarks helps maintain transparency and reduces risks of unmonitored capability advances.

Skynet Date (+0 days): Enhanced evaluation frameworks may slow deployment of inadequately tested AI systems by establishing higher standards for capability assessment. However, the impact on timeline is modest as this is primarily infrastructure building rather than direct safety intervention.

AGI Progress (+0.02%): The program accelerates AI research by providing compute and resources typically unavailable in academic settings, with projects targeting key AGI-relevant challenges like code optimization and general reasoning (ARC-AGI). Better evaluation tools also help identify and address capability gaps more effectively.

AGI Date (+0 days): By removing resource constraints for promising AI research projects and focusing on capability evaluation that drives progress, the program modestly accelerates the pace of AI development. The emphasis on benchmarking helps researchers identify and pursue productive research directions more efficiently.

Skynet Chance (+0.05%): The massive scale of infrastructure investment ($1.4 trillion) and rapid capability expansion into robotics, devices, and autonomous systems significantly increases potential attack surfaces and deployment of powerful AI in physical domains. The sheer concentration of compute resources in one organization also increases risks from single points of control failure.

Skynet Date (-1 days): The unprecedented $1.4 trillion infrastructure commitment represents a dramatic acceleration in compute availability for frontier AI development, potentially compressing timelines significantly. Expansion into robotics and autonomous physical systems could accelerate the transition from digital-only AI to AI with real-world actuators.

AGI Progress (+0.04%): The $1.4 trillion infrastructure commitment represents one of the largest resource allocations in AI history, directly addressing the primary bottleneck to AGI development: compute availability. OpenAI's expansion into diverse domains (robotics, scientific discovery, enterprise) suggests confidence in near-term breakthrough capabilities.

AGI Date (-1 days): This massive compute infrastructure investment dramatically accelerates the timeline by removing resource constraints that typically limit experimental scale. The 8-year timeline with hundreds of billions in projected 2030 revenue suggests OpenAI expects transformative capabilities within this decade, likely implying AGI arrival before 2033.

Skynet Chance (+0.01%): More efficient AI architectures could enable wider deployment and accessibility of powerful AI systems, slightly increasing proliferation risks. However, the focus on efficiency rather than raw capability growth presents minimal direct control challenges.

Skynet Date (+0 days): The development of more efficient AI architectures that reduce compute requirements could accelerate deployment timelines for advanced systems. The reported 1,000+ tokens per second throughput suggests faster iteration cycles for AI development.

AGI Progress (+0.02%): This represents meaningful architectural innovation that addresses key bottlenecks in AI systems (latency and compute efficiency), demonstrating alternative pathways to capability scaling. The ability to process operations in parallel rather than sequentially could enable handling more complex reasoning tasks.

AGI Date (+0 days): Diffusion-based approaches offering significantly better efficiency and parallelization could accelerate AGI timelines by making larger-scale experiments more economically feasible. The substantial funding and high-profile backing suggest this approach will receive serious resources for rapid development.

Skynet Chance (+0.04%): The research reveals that current AI agents are vulnerable to manipulation and perform poorly in complex, unsupervised scenarios, which could lead to unintended behaviors when deployed at scale. However, the proactive identification of these vulnerabilities through systematic testing slightly increases awareness of control challenges before widespread deployment.

Skynet Date (+1 days): The discovery of significant limitations in current agentic systems suggests that autonomous AI deployment will require more development and safety work than anticipated, potentially slowing the timeline for widespread unsupervised AI agent adoption. The need for explicit instructions and poor collaboration capabilities indicate substantial technical hurdles remain.

AGI Progress (-0.03%): The findings demonstrate fundamental limitations in current leading models' ability to handle complexity, make decisions under information overload, and collaborate autonomously—all critical capabilities for AGI. These revealed weaknesses suggest current architectures may be further from general intelligence than previously assessed.

AGI Date (+1 days): The research exposes significant capability gaps in state-of-the-art models that will need to be addressed before achieving AGI-level autonomous reasoning and collaboration. These findings suggest additional research and development cycles will be required, potentially extending the timeline to AGI achievement.

Skynet Chance (+0.01%): Increased AI compute infrastructure expands the potential for more powerful AI systems to be deployed, but the focus on regulated, sovereign infrastructure with known partners provides some oversight mechanisms. The net effect is a marginal increase in capability deployment with moderate governance.

Skynet Date (-1 days): Large-scale deployment of 10,000 advanced Blackwell GPUs accelerates the availability of high-performance AI inferencing infrastructure, making powerful AI systems more accessible to industrial applications sooner. This represents meaningful acceleration of AI capability deployment in Europe.

AGI Progress (+0.02%): Deployment of large-scale GPU infrastructure with Nvidia's latest Blackwell architecture represents significant expansion of compute resources available for advanced AI development and deployment. The 50% increase in Germany's AI computing power enables more ambitious AI research and applications.

AGI Date (-1 days): The €1 billion investment in cutting-edge GPU infrastructure with 10,000 Blackwell GPUs accelerates the timeline by making advanced compute more readily available for AI development starting in early 2026. This infrastructure expansion removes compute bottlenecks that could slow AGI research progress.