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

Skynet Chance (-0.03%): Increased AI literacy and education across broader student populations could lead to more informed development practices and awareness of risks, though it also accelerates the number of people capable of building advanced AI systems. The net effect is slightly positive for safety as understanding risks is the first step toward mitigation.

Skynet Date (-1 days): The massive educational shift toward AI, particularly China's aggressive integration of AI literacy across institutions, will significantly accelerate the development of AI capabilities by producing more AI-trained talent entering the workforce. This educational arms race, especially with 60% of Chinese students already using AI tools daily, compresses the timeline for advanced AI development.

AGI Progress (+0.03%): The systematic integration of AI education at scale, particularly in China where it's now mandatory at top institutions, represents a fundamental shift in human capital development that will accelerate AGI research. More AI-literate graduates entering the field with specialized training creates a stronger talent pipeline for AGI development than traditional CS programs.

AGI Date (-1 days): The rapid expansion of AI-specific degree programs and mandatory AI coursework, especially China's aggressive approach with nearly 60% daily AI tool usage among students, will dramatically accelerate the pace of AGI development by creating a larger, more specialized workforce. This educational transformation represents a structural acceleration in the AGI timeline as universities shift from debating AI integration to producing thousands of AI-specialized graduates annually.

Skynet Chance (+0.04%): The deliberate removal of safety guardrails and leadership's explicit rejection of safety measures increases risks of uncontrolled AI behavior and potential misuse. A major AI company actively deprioritizing alignment and safety research represents a meaningful increase in scenarios where AI systems could cause harm through loss of proper constraints.

Skynet Date (-1 days): The rapid deployment of less constrained AI systems without safety oversight could accelerate the timeline to potential control problems. However, xAI's relatively smaller market position compared to leading AI labs limits the magnitude of this acceleration effect.

AGI Progress (-0.01%): Employee departures including co-founders and engineers, combined with reports of lack of direction and being "stuck in catch-up phase," suggest organizational dysfunction that hinders technical progress. This represents a minor setback in one company's contribution to overall AGI development.

AGI Date (+0 days): The loss of key technical talent and organizational chaos at xAI slightly slows overall AGI timeline by reducing the effective number of competitive research teams making progress. The effect is modest given xAI's current position relative to frontier labs like OpenAI, Google DeepMind, and Anthropic.

Skynet Chance (+0.06%): The disbanding of OpenAI's mission alignment team and departure of safety-focused personnel reduces organizational capacity for AI alignment work and safety oversight, increasing risks of misaligned AI development. The loss of experienced talent who opposed potentially risky features like "adult mode" suggests weakening internal safety governance.

Skynet Date (-1 days): The departure of safety-focused personnel and dissolution of alignment teams may remove internal friction that slows deployment of advanced capabilities, potentially accelerating the timeline for deploying powerful but insufficiently aligned systems. However, the organizational chaos may also create some temporary delays in capability development.

AGI Progress (-0.05%): Mass departures of founding team members and key personnel represent significant loss of institutional knowledge and technical expertise at leading AI companies, likely slowing research progress and capability development. Organizational instability and brain drain typically impede complex technical advancement toward AGI.

AGI Date (+0 days): The loss of half of xAI's founding team and key OpenAI personnel will likely create organizational disruption, knowledge gaps, and slower development cycles, pushing AGI timelines somewhat later. Talent exodus typically delays complex projects as companies rebuild teams and restore momentum.

Skynet Chance (+0.04%): The disbanding of OpenAI's mission alignment team and departure of safety-focused personnel suggests reduced organizational focus on AI safety and alignment, which are critical safeguards against uncontrolled AI development. Leadership instability across major AI labs may compromise long-term safety priorities in favor of competitive pressures.

Skynet Date (-1 days): While safety team departures are concerning, organizational chaos and talent loss could paradoxically slow capability development in the short term. However, the weakening of alignment-focused teams may accelerate deployment of insufficiently controlled systems, creating a modest net acceleration of risk timelines.

AGI Progress (-0.01%): Loss of half of xAI's founding team and significant departures from OpenAI represent setbacks to institutional knowledge and research continuity at leading AI labs. Brain drain and organizational disruption typically slow technical progress, though the impact may be temporary if talent redistributes within the industry.

AGI Date (+0 days): Significant talent exodus and organizational restructuring at major AI companies creates friction and reduces research velocity in the near term. The disruption to team cohesion and loss of experienced researchers suggests a modest deceleration in the pace toward AGI development.