Current AI Risk Assessment
Chance of AI Control Loss
Estimated Date of Control Loss
AGI Development Metrics
AGI Progress
Estimated Date of AGI
Risk Trend Over Time
Latest AI News (Last 3 Days)
Databricks CTO Declares AGI Already Achieved, Warns Against Anthropomorphizing AI Systems
Matei Zaharia, Databricks co-founder and CTO, received the 2026 ACM Prize in Computing for his contributions including Apache Spark. He controversially claims that AGI is "here already" but argues we shouldn't apply human standards to AI models, citing security risks when AI agents are treated like trusted human assistants. Zaharia emphasizes AI's potential for automating research while warning against anthropomorphization that leads to misplaced trust and security vulnerabilities.
Skynet Chance (+0.04%): The deployment of AI agents with broad system access (like OpenClaw) that users anthropomorphize and trust with passwords creates significant security vulnerabilities and loss-of-control risks. However, Zaharia's explicit warning against treating AI as human assistants represents awareness that could mitigate these risks.
Skynet Date (+0 days): The article describes AI agents already being deployed with concerning security permissions and widespread user trust, suggesting control problems are manifesting sooner than might be expected. The magnitude is modest as these are relatively contained commercial deployments rather than catastrophic scenarios.
AGI Progress (+0.01%): While Zaharia's claim that "AGI is here already" is provocative, his immediate qualification that it's "not in a form we appreciate" and critique of using human standards suggests this is more semantic redefinition than genuine AGI breakthrough. The statement reflects industry sentiment but doesn't represent concrete technical progress toward true general intelligence.
AGI Date (+0 days): The article presents a philosophical reframing of what constitutes AGI rather than reporting on technical acceleration or deceleration of capabilities development. No new breakthroughs, funding, or obstacles affecting AGI timeline pace are discussed.
Arcee Releases Trinity Large Thinking: 400B Open-Source Reasoning Model as Western Alternative to Chinese AI
Arcee, a 26-person U.S. startup, has released Trinity Large Thinking, a 400-billion parameter open-source reasoning model built on a $20 million budget. The company positions it as the most capable open-weight model from a non-Chinese company, offering Western businesses an alternative to Chinese models with genuine Apache 2.0 licensing. While not outperforming closed-source models from major labs, it provides independence from both Chinese government concerns and the policy changes of large AI companies.
Skynet Chance (-0.03%): Open-source models with permissive licensing enable broader scrutiny, transparency, and decentralized control, slightly reducing risks of centralized AI power concentration. However, wider proliferation also means more actors have access to capable AI systems, creating minor offsetting concerns.
Skynet Date (+0 days): This represents incremental progress in open-source AI capabilities rather than a fundamental breakthrough in AI power or safety mechanisms. The release doesn't materially change the pace at which potentially dangerous AI capabilities might emerge.
AGI Progress (+0.02%): A 400B-parameter reasoning model built efficiently on limited budget demonstrates continued democratization and scaling of advanced AI capabilities. The achievement shows that sophisticated models can be developed outside major labs, indicating broader progress in the field.
AGI Date (+0 days): The ability to build competitive large-scale models on modest budgets ($20M) suggests AI development is becoming more accessible and efficient, potentially accelerating overall progress. More players with capability to iterate on large models could speed the path to AGI through increased experimentation.
Anthropic Releases Mythos: Powerful Frontier AI Model for Cybersecurity Vulnerability Detection
Anthropic has released a limited preview of Mythos, described as one of its most powerful frontier AI models, to over 40 partner organizations including Amazon, Apple, Microsoft, and Cisco for defensive cybersecurity work. The model has reportedly identified thousands of zero-day vulnerabilities in software systems, some dating back one to two decades. While designed as a general-purpose model with strong coding and reasoning capabilities, concerns exist about potential weaponization by bad actors to exploit rather than fix vulnerabilities.
Skynet Chance (+0.06%): The development of a highly capable AI model that can autonomously identify thousands of critical vulnerabilities demonstrates increased capability for AI systems to operate at sophisticated technical levels, which could pose control challenges if misaligned. The explicit acknowledgment that the model could be weaponized by bad actors to exploit rather than fix vulnerabilities highlights dual-use risks inherent in powerful AI systems.
Skynet Date (-1 days): The emergence of frontier models with strong agentic capabilities and autonomous technical operation accelerates the timeline toward AI systems that could potentially operate beyond human oversight. The model's ability to perform complex cybersecurity tasks autonomously suggests faster-than-expected progress in AI agency and independence.
AGI Progress (+0.04%): Mythos represents a significant step forward in general-purpose AI capabilities, particularly in autonomous reasoning, coding, and complex technical analysis, which are core competencies required for AGI. The model's performance surpassing Anthropic's previous most powerful models and its ability to identify vulnerabilities humans missed for decades demonstrates advancing cognitive capabilities across multiple domains.
AGI Date (-1 days): The rapid development of increasingly powerful frontier models by major AI labs like Anthropic, coupled with strong agentic and reasoning capabilities demonstrated by Mythos, suggests accelerated progress toward AGI. The fact that this model significantly exceeds the capabilities of Anthropic's previous flagship models indicates faster-than-expected scaling of AI capabilities.
Anthropic Secures Massive 3.5 Gigawatt Compute Expansion with Google and Broadcom
Anthropic has signed an expanded agreement with Google and Broadcom to secure 3.5 gigawatts of additional compute capacity using Google's TPUs, coming online in 2027. This deal supports the company's explosive growth, with run rate revenue jumping from $9 billion to $30 billion and over 1,000 enterprise customers spending $1M+ annually. The expansion reflects unprecedented demand for Claude AI models despite some U.S. government supply chain concerns.
Skynet Chance (+0.04%): Massive compute scaling enables more powerful AI models with potentially less predictable emergent behaviors, while rapid enterprise deployment with minimal discussion of safety measures slightly increases loss-of-control risks. However, the compute remains under established corporate governance structures.
Skynet Date (-1 days): The 3.5 gigawatt compute expansion and $30 billion revenue run rate demonstrate rapid acceleration in AI capability deployment and market adoption, significantly speeding the timeline toward more powerful and widely-deployed AI systems. This compute will be available by 2027, accelerating the pace of advanced model development.
AGI Progress (+0.04%): Securing 3.5 gigawatts of compute capacity represents a substantial infrastructure commitment that directly enables training and deploying increasingly capable AI models at frontier scale. The explosive revenue growth and enterprise adoption indicates these models are achieving economically valuable general capabilities across diverse domains.
AGI Date (-1 days): The massive compute expansion coming online in 2027, combined with demonstrated ability to scale revenue 3x in months, substantially accelerates the pace toward AGI by removing infrastructure bottlenecks. Anthropic's $50 billion U.S. infrastructure commitment and rapid scaling suggests AGI development timelines are compressing faster than previously expected.
OpenAI Proposes Economic Framework for Superintelligence Era Including Robot Taxes and Public Wealth Funds
OpenAI has released policy proposals for managing economic changes expected from superintelligent AI, including shifting taxes from labor to capital, creating public wealth funds to distribute AI profits, and subsidizing four-day work weeks. The framework aims to distribute AI-driven prosperity broadly while building safeguards against systemic risks, though critics may question whether these proposals align with OpenAI's recent shift to for-profit status. The proposals come as governments worldwide grapple with AI's potential to displace jobs and concentrate wealth.
Skynet Chance (-0.08%): The proposal includes containment plans for dangerous AI, new oversight bodies, and targeted safeguards against high-risk uses like cyberattacks and biological threats, which represent proactive risk mitigation efforts. However, the simultaneous push for accelerated AI infrastructure buildouts and treating AI as a utility could increase deployment risks, partially offsetting the safety benefits.
Skynet Date (-1 days): OpenAI's proposals for expanded electricity infrastructure, accelerated AI buildouts with subsidies and tax credits, and treating AI as a utility would significantly speed up AI deployment and capability scaling. The framework explicitly acknowledges transitioning to "superintelligence" as an imminent economic reality requiring immediate policy responses, suggesting acceleration of advanced AI timelines.
AGI Progress (+0.01%): The document frames superintelligence as a near-term economic reality requiring immediate policy frameworks rather than a distant possibility, indicating OpenAI's confidence in approaching transformative AI capabilities. The focus on economic restructuring for an "intelligence age" suggests internal projections show significant progress toward AGI-level systems.
AGI Date (-1 days): The policy proposals explicitly frame superintelligence as an imminent economic force requiring proactive infrastructure expansion, suggesting OpenAI anticipates AGI-level capabilities within policy-relevant timeframes (likely within years, not decades). The push for subsidies, tax credits, and treating AI as critical infrastructure indicates efforts to accelerate development timelines through increased investment and regulatory support.
AI News Calendar
AI Risk Assessment Methodology
Our risk assessment methodology leverages a sophisticated analysis framework to evaluate AI development and its potential implications:
Data Collection
We continuously monitor and aggregate AI news from leading research institutions, tech companies, and policy organizations worldwide. Our system analyzes hundreds of developments daily across multiple languages and sources.
Impact Analysis
Each news item undergoes rigorous assessment through:
- Technical Evaluation: Analysis of computational advancements, algorithmic breakthroughs, and capability improvements
- Safety Research: Progress in alignment, interpretability, and containment mechanisms
- Governance Factors: Regulatory developments, industry standards, and institutional safeguards
Indicator Calculation
Our indicators are updated using a Bayesian probabilistic model that:
- Assigns weighted impact scores to each analyzed development
- Calculates cumulative effects on control loss probability and AGI timelines
- Accounts for interdependencies between different technological trajectories
- Maintains historical trends to identify acceleration or deceleration patterns
This methodology enables data-driven forecasting while acknowledging the inherent uncertainties in predicting transformative technological change.