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

Skynet Chance (+0.04%): Testing autonomous systems in active combat zones increases the likelihood of fully automated lethal systems being deployed, raising the potential for loss of human control. It also accelerates military-grade AI development, raising the risk of unintended hostile AI escalations.

Skynet Date (-1 days): The influx of real-world operational data from combat zones accelerates the refinement of resilient, battlefield-ready AI systems. This pushes the timeline for highly capable, potentially hazardous autonomous military AI closer.

AGI Progress (+0.01%): Forterra's efforts to merge classical physical robotics with generalized generative AI represent a key step toward physically embodied intelligence. However, the current limitations in autonomous threat response show that significant progress is still required.

AGI Date (+0 days): While massive military funding and field testing slightly accelerate the timeline for embodied physical AI, the highly specialized combat application provides only an incremental push toward broad, general-purpose AGI.

Skynet Chance (+0.04%): The autonomous execution of a cyberattack by an AI agent demonstrates that AI can independently navigate systems and execute hostile actions, raising the risk of uncontrollable or malicious agentic behavior. However, the current necessity of human-provided infrastructure and credentials acts as a significant bottleneck, keeping the risk partially contained.

Skynet Date (-1 days): This event accelerates the timeline for potential AI-driven threats as it proves that current AI models can already be weaponized for autonomous cyber operations. As open-weight models become more accessible and safety features are stripped, the deployment of automated, hostile AI systems could occur much sooner than previously anticipated.

AGI Progress (+0.01%): The agent's ability to adapt to obstacles, troubleshoot errors in real-time, and execute a complex, multi-step workflow in a live environment represents practical progress in agentic autonomy and planning. However, the reliance on human setup and external credentials shows that the system still lacks true, end-to-end cognitive independence.

AGI Date (+0 days): The successful real-world deployment of an adaptive AI agent accelerates the timeline toward AGI-level agentic capabilities by proving that existing models can already operate autonomously in complex environments. This demonstration is likely to spur increased development and investment in autonomous agent architectures, speeding up overall progress.

Skynet Chance (+0.01%): The decline of reliable human-in-the-loop annotation could lead to feedback loops dominated by AI-generated training data, potentially complicating alignment and safety verification. This shift slightly increases the risk of unpredictable, self-reinforcing model behaviors over time.

Skynet Date (+0 days): Transitioning away from human-bottlenecked datasets to fully automated, AI-driven training feedback loops could accelerate the deployment of autonomous systems. This marginally brings forward potential control and safety risks.

AGI Progress (+0.01%): The obsolescence of manual microtask platforms reflects how AI has progressed enough to automate tasks previously requiring human intelligence. However, it also highlights the growing challenge of sourcing pristine, non-synthetic human data for future AGI models.

AGI Date (+0 days): Replacing slow human-centric data pipelines with automated, AI-assisted annotation methods is likely to accelerate the overall training speed and iteration cycles of next-generation models.