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

Skynet Chance (-0.03%): Leadership instability and talent departures at a major AI lab may slow development of advanced capabilities and reduce the likelihood of unchecked rapid advancement. The organizational chaos and product issues suggest less effective progress toward potentially dangerous systems.

Skynet Date (+0 days): The loss of technical talent and internal challenges at xAI will likely slow the company's AI development pace, marginally decelerating the overall timeline toward advanced AI systems. However, the impact is limited as other labs continue their work unaffected.

AGI Progress (-0.02%): The departure of nearly half the founding team from a well-funded AI lab represents a setback in collective research capacity and institutional knowledge. This brain drain, combined with product struggles, indicates reduced momentum in advancing AI capabilities at xAI.

AGI Date (+0 days): While xAI's internal challenges may slow its specific contributions to AGI development, the broader AI ecosystem remains robust with OpenAI and Anthropic continuing their progress. The overall timeline impact is minimal but slightly positive as one major player loses momentum.

Skynet Chance (-0.03%): This tool focuses on improving human oversight and understanding of AI-generated code, which marginally enhances control and transparency over AI agent outputs. By providing context and review mechanisms, it slightly reduces the risk of uncontrolled AI behavior in software development contexts.

Skynet Date (+0 days): The tool aims to add oversight layers to AI agent workflows, which could slightly slow down unfettered AI agent autonomy by requiring human review checkpoints. However, the impact on overall timeline is minimal as it's primarily a management tool rather than a fundamental capability constraint.

AGI Progress (+0.01%): The need for such infrastructure indicates AI coding agents are now producing code volumes beyond human comprehension capacity, suggesting significant progress in autonomous AI capabilities. The fact that this problem requires a $60M solution demonstrates AI agents have reached practical, production-scale autonomy in software development.

AGI Date (+0 days): By solving the code management bottleneck created by AI agents, this tool enables wider adoption and deployment of AI coding agents at scale. Removing friction in AI agent integration into workflows could marginally accelerate progress toward more general autonomous systems.

Skynet Chance (+0.04%): World models that can predict and plan for future events represent advancement toward more autonomous AI systems with greater agency, potentially increasing risks if deployed without robust alignment and control mechanisms. The expansion into robotics and critical infrastructure domains like medicine and energy amplifies potential consequences of misaligned systems.

Skynet Date (-1 days): The significant funding and compute expansion accelerates development of world models capable of planning and prediction, potentially shortening timelines to more capable autonomous systems. However, the focus remains primarily on commercial applications rather than pure capability advancement, moderating the acceleration effect.

AGI Progress (+0.04%): World models are widely considered a critical advancement beyond current LLM limitations, as they enable AI systems to build internal representations and plan for future states rather than just pattern matching. Runway's success in outperforming Google and OpenAI on benchmarks, combined with substantial funding for scaling, represents meaningful progress toward more general AI capabilities.

AGI Date (-1 days): The $315M funding specifically targeting world model pre-training, combined with expanded compute infrastructure via CoreWeave partnership and aggressive hiring plans, directly accelerates the pace of research in a technology area viewed as essential for AGI. The competitive landscape with World Labs and DeepMind also intensifies the overall race toward more capable systems.

Skynet Chance (+0.04%): Massive capital infusion accelerates capability development at a frontier lab building autonomous agents, potentially outpacing safety research and alignment work. The competitive pressure to deploy powerful systems quickly increases risks of insufficient safety testing before release.

Skynet Date (-1 days): The $20 billion funding specifically targeting compute resources and the intense competitive race between frontier labs significantly accelerates the timeline for developing highly capable AI systems. This rapid escalation of resources and competitive pressure compresses the development timeline for potentially dangerous capabilities.

AGI Progress (+0.04%): The unprecedented $20 billion raise demonstrates both the viability of scaling approaches and provides enormous resources for compute and talent acquisition at a leading frontier lab. Recent successes with coding agents and research models show concrete progress toward general-purpose AI capabilities.

AGI Date (-1 days): The doubling of fundraising targets and massive compute investment directly accelerates AGI timeline by removing capital constraints on scaling experiments. The competitive dynamics with OpenAI's $100 billion round creates a race condition that prioritizes speed over measured development.

Skynet Chance (-0.03%): The moratorium, if enacted, would slightly reduce uncontrolled AI infrastructure expansion, potentially allowing more time for safety oversight and governance frameworks to develop alongside capability growth. However, this is a localized policy with uncertain prospects and won't fundamentally alter AI safety alignment challenges.

Skynet Date (+1 days): Slowing data center construction in multiple states could modestly decelerate the pace of AI scaling by constraining compute infrastructure availability, potentially pushing timelines for advanced AI systems slightly further out. The effect is limited as development can shift to other jurisdictions or countries.

AGI Progress (-0.01%): Restricting data center construction represents a minor obstacle to scaling AI systems, as compute infrastructure is essential for training larger models. However, the impact is minimal given this affects only select states and companies can relocate infrastructure investments elsewhere.

AGI Date (+0 days): Infrastructure constraints from multi-state moratoriums could modestly slow the pace of AI capability scaling by limiting available compute resources for training advanced models. The deceleration effect is small since major AI labs can build internationally or in unaffected regions.