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

Skynet Chance (+0.04%): Authorizing autonomous swarms of agents to run continuously in the background increases the probability of unforeseen system drift and loss of human control. This recursive prompting structure makes monitoring and alignment significantly more complex.

Skynet Date (-1 days): Deploying continuous, self-correcting agent loops accelerates the timeline toward uncontrollable AI systems by bypassing traditional checkpoints and human-in-the-loop oversight. This rapid operational autonomy shortens the runway for developing robust containment safety measures.

AGI Progress (+0.04%): Transitioning to agentic loops represents a major conceptual milestone toward AGI by moving beyond static Q&A to continuous, self-improving cognitive workflows. This approach effectively leverages scaling compute at inference time to overcome previously hard barriers in logic and coding.

AGI Date (-1 days): Automating software engineering and system optimization through non-stop agent swarms will compress the timeline to AGI by compounding daily development gains. This continuous operational model accelerates the practical capabilities of current LLMs much faster than traditional manual development.

Skynet Chance (0%): The restructuring and funding of an AI infrastructure provider do not directly alter the core likelihood of an uncontrollable AI scenario. Therefore, the impact on the probability of a Skynet-like event is neutral.

Skynet Date (+0 days): Massive investment in scaling up global inference networks makes running advanced models cheaper and more accessible. This democratization and expansion of compute power could marginally accelerate the timeline of deployment-related risks.

AGI Progress (+0.01%): The injection of capital and restructuring ensures the continued expansion of high-performance inference networks necessary for running and scaling complex models. This strengthens the underlying infrastructure needed to achieve AGI.

AGI Date (+0 days): By increasing the availability of specialized cloud services, researchers can iterate and deploy large-scale AI models faster. This keeps the industry on an accelerated path toward AGI development.

Skynet Chance (+0.04%): Distributing frontier-class AI capabilities via open-weight models makes it far more difficult to enforce centralized safety guardrails or recall rogue systems. This decentralized access increases the risk of malicious fine-tuning and alignment evasion, raising the likelihood of uncontrollable scenarios.

Skynet Date (-1 days): Rapidly empowering open-source developers with top-tier hardware accelerates the timeline wherein potentially dangerous, unaligned models could be released to the public. This compressed timeframe reduces the window available for global safety standards and defense mechanisms to mature.

AGI Progress (+0.03%): Providing a highly capable startup with billions of dollars in cutting-edge compute directly accelerates the training of massive neural networks. This massive influx of hardware allows open-source research to aggressively push the boundaries of general intelligence capabilities.

AGI Date (-1 days): The injection of massive computer power into another highly competitive lab intensifies the global AI race, pulling the projected timeline for AGI forward. With more actors possessing scale-level compute, breakthrough models are likely to emerge sooner than previously expected.

Skynet Chance (-0.03%): The forced shutdown of Anthropic's advanced models demonstrates that governments can successfully intervene and halt the deployment of frontier AI systems, slightly lowering the immediate risk of uncontrolled AI deployment. However, the chaotic and potentially political nature of the intervention limits its systemic safety benefit.

Skynet Date (+1 days): Forcing state-of-the-art models offline delays their widespread integration into critical infrastructure and potential misuse, decelerating the timeline toward catastrophic scenarios. Conversely, the reduction in defensive cybersecurity capabilities could leave systems vulnerable to other malicious actors in the interim.

AGI Progress (-0.04%): Restricting access to Anthropic's latest frontier models represents a setback for open AGI research and developer integration, limiting the active feedback loop necessary for capability scaling. Although the underlying research remains intact, halting deployment slows down real-world progress.

AGI Date (+1 days): The sudden enforcement of export controls and government shutdowns of frontier models injects regulatory instability into the AI industry, decelerating the pace of AGI development. Labs may now have to divert resources toward compliance and navigating political disputes rather than raw technical scaling.

Skynet Chance (-0.03%): Jumper's move to Anthropic, a lab historically focused on safety and alignment, could marginally strengthen efforts to prevent runaway AI scenarios. However, the lateral transfer of a single researcher between top-tier labs does not fundamentally alter the systemic probability of global AI control loss.

Skynet Date (+0 days): Since this is a transfer of existing talent between established, safety-conscious frontier labs rather than a new technological risk factor, it has a negligible impact on the timeline toward potential existential threats.

AGI Progress (+0.01%): The redistribution of a world-class scientific mind like Jumper to Anthropic can spark fresh collaborative synergies, incrementally advancing complex reasoning and scientific AI capabilities. It underscores the concentration of elite expertise dedicated to pushing frontier AI boundaries.

AGI Date (+0 days): The intensifying talent war and aggressive poaching among DeepMind, OpenAI, and Anthropic are likely to compress development cycles. This heightened competitive pressure pushes companies to accelerate their respective timelines for achieving AGI-level capabilities.