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

Skynet Chance (+0.01%): Drastically reducing energy requirements could democratize the deployment of highly advanced AI models, making oversight and safety regulation harder to enforce globally. This decentralization slightly increases the long-term risk of uncontrollable or malicious AI deployments.

Skynet Date (-1 days): By potentially removing the energy constraints that threaten to stall AI growth, this technology could accelerate the development timeline toward potentially hazardous, autonomous systems.

AGI Progress (+0.03%): Energy consumption is currently a primary constraint on AI scaling, making a potential 1,000x efficiency improvement a major leap forward for running AGI-scale workloads.

AGI Date (-1 days): Solving the power bottleneck would allow massive, rapid expansion of compute infrastructure, significantly pulling forward the timeline for achieving AGI.

Skynet Chance (+0.04%): Training general AI models on action-labeled simulated environments dramatically lowers the barrier to creating highly capable physical agents. Although the company bans military use, the underlying technology of cross-domain embodiment increases the long-term risk of uncontrollable physical AI agents.

Skynet Date (-1 days): Using vast libraries of video game data as a training shortcut bypasses the slow and expensive process of collecting real-world physical data. This methodological acceleration brings the timeline for highly capable, physically embodied autonomous systems closer.

AGI Progress (+0.03%): The ability of a single model to generalize spatial-temporal reasoning from game engines to real-world physical embodiments marks a significant leap toward generalized physical agency. By leveraging action-labeled gameplay, the model successfully bridges the gap between digital reasoning and physical execution.

AGI Date (-1 days): A massive capital injection coupled with a virtually infinite, pre-labeled dataset of human actions accelerates the timeline for achieving general physical intelligence. This bypasses traditional data bottlenecks in robotics, potentially bringing AGI-like physical capabilities closer.

Skynet Chance (+0.01%): Expanding global compute infrastructure increases the capacity to train more powerful, potentially uncontrollable AI systems. However, infrastructure growth itself does not inherently alter the alignment paradigm, resulting in only a minor increase in overall risk.

Skynet Date (-1 days): The massive influx of capital into global data center infrastructure accelerates the hardware scaling necessary to train advanced models, potentially shortening the timeline to uncontrollable AI. This competitive rush to expand physical compute capabilities brings the risk horizon closer.

AGI Progress (+0.02%): Massive hardware and infrastructure expansion directly fuels the compute-scaling laws necessary for progressing toward AGI. By broadening data center capacity globally, tech giants are building the physical foundation required for next-generation AI.

AGI Date (-1 days): This significant capital deployment accelerates the timeline to AGI by rapidly overcoming the physical compute bottlenecks currently limiting model training. The competitive infrastructure race among tech giants in India will likely compress the time needed to develop advanced systems.

Skynet Chance (0%): The migration of researchers between leading AI companies redistributes expertise but does not inherently alter the fundamental likelihood of creating uncontrollable or hostile AI systems.

Skynet Date (+0 days): Concentrating top talent in highly competitive, fast-moving startups could accelerate frontier AI capabilities, potentially outstripping the development of necessary safety and alignment frameworks.

AGI Progress (+0.01%): Consolidating elite researchers from Google into focused, mission-driven labs like Anthropic and OpenAI is likely to enhance collective research synergy and lead to incremental capability gains.

AGI Date (+0 days): The influx of experienced developers to agile startups preparing for public offerings will likely hasten the timeline to AGI by streamlining the development of next-generation models.

Skynet Chance (+0.01%): The widespread commercial deployment of physical humanoid robots increases the potential real-world impact surface if control is ever lost. The growth of physical AI infrastructure provides the necessary hardware substrate for potential future physical disruption.

Skynet Date (-1 days): Massive capital injection into humanoid manufacturing accelerates the timeline for deploying physical AI systems into the human environment. This rapid commercialization outpaces the development of robust physical safety frameworks, potentially accelerating physical AI risk timelines.

AGI Progress (+0.02%): Securing substantial funding to scale humanoid robots provides a critical physical testing ground and data pipeline for embodied AI, which is essential for general intelligence. Real-world feedback from thousands of deployed units will accelerate the training of more generalized physical foundation models.

AGI Date (-1 days): The rapid commercialization and deployment of humanoid hardware will significantly speed up the collection of real-world interaction data. This abundance of physical interaction data is expected to accelerate the timeline for achieving physically grounded AGI.

Skynet Chance (+0.01%): Lowering inference costs and optimizing hardware enables wider, more pervasive deployment of agentic AI systems, marginally increasing the systemic risks of uncontrolled model behavior.

Skynet Date (-1 days): By reducing costs and increasing efficiency of running complex models, this development accelerates the deployment timelines of sophisticated AI agents, potentially hastening the arrival of safety-critical scenarios.

AGI Progress (+0.02%): Designing custom, highly efficient silicon tailored for OpenAI's specific workloads provides the computational foundation necessary to run increasingly complex and agentic AI models closer to real-time.

AGI Date (-1 days): Accelerating inference speeds and lowering operational costs will likely speed up the deployment, refinement, and testing cycles of frontier models, bringing the achievement of AGI closer.

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.