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

Skynet Chance (-0.03%): Government intervention to halt models with bypassed guardrails demonstrates active regulatory oversight, which could reduce the likelihood of releasing uncontrollable AI.

Skynet Date (+1 days): Enforced removal of advanced models due to security vulnerabilities delays their widespread deployment, thereby decelerating the potential timeline toward an uncontrolled AI scenario.

AGI Progress (-0.03%): Forcing the withdrawal of Anthropic's cutting-edge models temporarily halts commercial and research access to advanced systems, representing a setback in overall AGI progress.

AGI Date (+0 days): Regulatory roadblocks and forced product recalls create friction that slows down the deployment and iterative improvement of AGI-enabling technologies.

Skynet Chance (-0.03%): The government's proactive ban on models with flawed guardrails establishes a regulatory safety net, slightly lowering the long-term risk of an uncontrollable AI incident.

Skynet Date (+1 days): Taking flawed models off the market delays the timeline for deploying advanced systems with potential vulnerabilities, slowing down the path to a critical failure event.

AGI Progress (-0.03%): The removal of Anthropic's flagship models from public access hinders developers' ability to build upon these advanced architectures, slowing immediate capabilities progress.

AGI Date (+0 days): Government intervention and compliance demands introduce significant delays in the commercial release cycle, pushing back the timeline for achieving AGI.

Skynet Chance (+0.01%): While the creation of the 'Strategic Futures' team aims to mitigate catastrophic risk, focusing on recursive self-improvement could introduce unpredictable dangers. Additionally, securing political insider status might lead to reduced external oversight, slightly increasing uncontrollable AI risks.

Skynet Date (-1 days): Acquiring a top-tier pioneer like Shazeer and actively researching recursive self-improvement could accelerate the timeline toward highly advanced and potentially uncontrollable AI systems. This concentration of elite capabilities and strategic maneuvering reduces the time available to establish robust external safety frameworks.

AGI Progress (+0.03%): Hiring Noam Shazeer, a foundational mind behind the Transformer architecture, significantly boosts OpenAI's technical research capabilities. Furthermore, the explicit focus of the new Strategic Futures team on recursive self-improvement directly targets a core mechanism for achieving AGI.

AGI Date (-1 days): The consolidation of elite technical talent and strategic government relations at OpenAI is poised to accelerate their research pipelines. This corporate alignment suggests that milestones on the path to AGI may be reached sooner than previously anticipated.

Skynet Chance (+0.01%): Accelerating energy infrastructure for data centers enables the deployment of increasingly massive AI models, potentially outpacing the development of alignment and control mechanisms. This rapid scaling, driven by infrastructure prioritisation over safety, marginally increases the long-term risk of uncontrollable AI.

Skynet Date (-1 days): By removing regulatory bottlenecks for grid connections, the mandate significantly compresses the timeline required to scale up next-generation AI systems. This acceleration in computational power deployment brings potential existential risks closer in time.

AGI Progress (+0.03%): Securing direct grid access solves a major physical bottleneck for the high-performance computing clusters necessary for training future AGI-class models. This regulatory shift directly supports the ongoing hardware scaling required to achieve advanced general intelligence.

AGI Date (-1 days): Fast-tracking energy access allows tech giants to bring massive new data centers online years ahead of schedule, directly accelerating the timeline for training frontier models. This policy removes a critical logistical barrier, pushing the expected arrival date of AGI significantly closer.

Skynet Chance (+0.01%): Developing autonomous agents with deep spatial-temporal reasoning increases the potential for AI to interact with and manipulate environments independently, slightly elevating control and alignment risks. However, since the technology is currently restricted to simulations, the immediate threat remains low.

Skynet Date (-1 days): A massive influx of capital and compute resources accelerates the development timeline of highly capable autonomous agents, potentially hastening the arrival of physical or virtual control risks.

AGI Progress (+0.02%): The utilization of vast, interactive first-person datasets to train AI agents in spatial-temporal reasoning represents a critical step forward in achieving embodied AGI.

AGI Date (-1 days): Securing substantial funding to scale compute capacity directly compresses the timeline for training sophisticated world models, accelerating the path to AGI.

Skynet Chance (-0.05%): The mobilization of tech workers advocating for safety guardrails and opposing autonomous warfare applications reduces the likelihood of unchecked, dangerous AI deployments. This grassroots pressure pushes the industry toward stronger alignment and regulatory compliance, mitigating existential risks.

Skynet Date (+1 days): The creation of a pro-safety super PAC and worker resistance against militarized AI can slow down the deployment of high-risk systems by imposing regulatory and political hurdles. This deceleration allows more time for safety frameworks to be established before dangerous capabilities are realized.

AGI Progress (-0.01%): Increased political scrutiny and demands for strict legislative guardrails could impose minor friction on rapid AI scaling and commercialization efforts. While not halting foundational research, it introduces compliance burdens that might slightly temper raw development speed.

AGI Date (+0 days): An increase in regulatory obstacles and worker-led pushback against aggressive deployment could push back the timeline for achieving AGI by prioritizing safety over rapid capability scaling. This adds regulatory delays to the overall development pipeline.

Skynet Chance (+0.03%): The push for "digital sovereignty" and decentralized AI development to bypass U.S. export controls could lead to fragmented global safety standards. This fragmentation makes coordinating international safety protocols more difficult, slightly increasing the risk of an unaligned or uncontrollable AI scenario.

Skynet Date (+1 days): U.S. government intervention blocking the export of advanced models like Anthropic's Mythos 5 slows down the global deployment and integration of high-risk AI capabilities. This political friction acts as a temporary buffer, delaying the timeline for potential catastrophic loss-of-control scenarios.

AGI Progress (-0.03%): Restrictions on exporting frontier models impede the global collaboration, funding, and commercial feedback loops necessary for rapid capability scaling. This administrative friction represents a minor setback in the practical progress toward building AGI.

AGI Date (+1 days): Geopolitical friction and unilateral export bans on cutting-edge models introduce regulatory bottlenecks that delay global distribution and testing of the latest AI iterations. This conflict is likely to decelerate the overall timeline for achieving widely accessible AGI.

Skynet Chance (+0.04%): By advancing AI's capability to accurately simulate and interact with physical environments, this technology enhances the potential for future physical-world agency, slightly increasing risks of uncontrollable physical actions. However, this remains a development milestone rather than an immediate threat of safety failure.

Skynet Date (-1 days): The massive funding injection and infrastructure support from Amazon will accelerate the development of physically grounded AI models, potentially shortening the timeline to systems with physical-world capabilities. This rapid pace of development brings the potential timeline for physical-control risks closer.

AGI Progress (+0.04%): Developing robust 'world models' is a critical milestone for AGI, transitioning AI from pure text-based comprehension to actual physical and spatial reasoning. This advancement bridges a key gap between purely virtual intelligence and real-world physical understanding.

AGI Date (-1 days): This massive capital injection and strategic partnership with Amazon for custom chip optimization will directly accelerate the research and deployment of world models. Consequently, this shortens the expected timeline for achieving multi-modal, physically grounded AGI.

Skynet Chance (+0.01%): Enabling AI models to successfully interact with and manipulate the physical world increases the potential real-world harm and control challenges if the AI system becomes misaligned.

Skynet Date (-1 days): By accelerating the collection of high-quality physical interaction data, this development speeds up the timeline for deploying capable, embodied AI agents that could pose physical control risks.

AGI Progress (+0.02%): Resolving the physical data bottleneck allows AI to transition from purely text-based reasoning to understanding and acting within the physical world, which is a key requirement for true AGI.

AGI Date (-1 days): Providing standardized, scaled datasets and collection pipelines for robotics shortens the timeline for achieving fully capable embodied AGI by bypassing a major development bottleneck.

Skynet Chance (-0.08%): By applying formal mathematical verification to AI outputs, this technology helps prevent unpredictable behavior and hallucinations, directly addressing the alignment problem. Standardizing deterministic constraints on top of chaotic neural networks reduces the likelihood of catastrophic, uncontrollable AI actions.

Skynet Date (+1 days): The development of robust verification frameworks acts as a decelerator for existential risks by forcing safety checkpoints before advanced systems can be deployed. This pushes back the timeline of potential uncontrollable scenarios by establishing rigorous, math-based control methods.

AGI Progress (+0.02%): Integrating formal verification with deep learning addresses a critical bottleneck in AGI development: the lack of reliable, deterministic reasoning. Overcoming the hallucination problem in complex domains represents a significant step forward in building highly capable, human-level cognitive systems.

AGI Date (+0 days): By providing a mathematical framework for AI reliability, this technology could accelerate the commercial adoption and development pace of advanced AI in scientific and legal fields. This systemized trust allows researchers to deploy and iterate on complex cognitive architectures much faster, potentially bringing forward the arrival of AGI.