Current AI Risk Assessment

25.95%

Chance of AI Control Loss

October 24, 2035

Estimated Date of Control Loss

AGI Development Metrics?

77.28%

AGI Progress

November 13, 2029

Estimated Date of AGI

Risk Trend Over Time

Latest AI News (Last 3 Days)

April 24, 2026
+0.09% Risk

Google Commits Up to $40B to Anthropic Amid Escalating AI Compute Race

Google plans to invest up to $40 billion in Anthropic, with $10 billion committed immediately at a $350 billion valuation and $30 billion contingent on performance targets. The investment includes providing 5 gigawatts of computing capacity over five years, following Anthropic's release of its most powerful model, Mythos, which has significant cybersecurity applications but restricted access due to misuse concerns. This deal is part of an intensifying competition for AI compute resources, with Anthropic securing multiple infrastructure partnerships including additional investments from Amazon totaling up to $100 billion in compute capacity.

DeepSeek Releases V4 Models With 1.6 Trillion Parameters, Approaching Frontier Performance at Lower Cost

Chinese AI lab DeepSeek has released preview versions of its V4 large language models, including V4 Pro with 1.6 trillion parameters, making it the largest open-weight model available. The models reportedly close the gap with leading frontier models on reasoning benchmarks while offering significantly lower pricing, though they trail state-of-the-art models by approximately 3-6 months in knowledge tests. The release comes amid U.S. accusations that China is stealing American AI intellectual property through proxy accounts.

Meta Commits to Millions of Amazon's Graviton AI CPUs in Major Cloud Deal

Meta has signed a deal with AWS to use millions of Amazon's homegrown Graviton ARM-based CPUs for AI workloads, particularly for inference and AI agent tasks. This marks a shift from GPU-dominated training workloads to CPU-intensive inference needs driven by AI agents performing real-time reasoning and multi-step coordination. The deal redirects Meta's spending back to AWS from competitors like Google Cloud, while showcasing Amazon's custom chip strategy against Nvidia's competing ARM-based AI CPUs.

April 23, 2026
+0.04% Risk

OpenAI Unveils GPT-5.5 with Enhanced Agentic Capabilities and Multi-Purpose 'Superapp' Vision

OpenAI released GPT-5.5, described as its smartest and most intuitive AI model yet, with significant improvements in agentic computing, coding, knowledge work, mathematics, and scientific research. The company positions this release as a step toward creating a unified "superapp" combining ChatGPT, Codex, and AI browser capabilities, while maintaining a rapid release cadence with new models appearing monthly. OpenAI's leadership suggests the pace of AI development has been "surprisingly slow" and expects extremely significant improvements in the medium term.

April 22, 2026
+0.12% Risk

Google Cloud Unveils Specialized TPU 8t and TPU 8i Chips for AI Training and Inference

Google Cloud announced its eighth generation tensor processing units (TPUs), splitting into two specialized chips: TPU 8t for model training and TPU 8i for inference. The new chips promise 3x faster training, 80% better performance per dollar, and support for clusters exceeding 1 million TPUs. Despite this advancement, Google continues to offer Nvidia's latest chips alongside its own custom processors, with both companies collaborating on networking optimization.

Google Integrates Gemini AI Agent into Enterprise Chrome Browser with Auto-Browse Capabilities

Google announced it will integrate Gemini AI-powered "auto browse" agentic capabilities into Chrome for enterprise users, enabling the AI to perform tasks like booking travel, data entry, and meeting scheduling across browser tabs. The feature requires human approval before final actions and will be available to Workspace users in the U.S., with Google also introducing security measures to detect unsanctioned AI tools in the workplace. Google emphasizes this will free workers for strategic tasks, though studies suggest AI may actually intensify workloads rather than reduce them.

Google Launches Gemini Enterprise Agent Platform for IT Teams at Cloud Next Conference

Google announced its Gemini Enterprise Agent Platform at the Cloud Next conference, a tool designed for building and managing AI agents at enterprise scale, positioning it as a competitor to Amazon Bedrock AgentCore and Microsoft Foundry. The platform is specifically targeted at IT and technical teams, while business users are directed to the separate Gemini Enterprise app for simpler agent-based tasks. The platform supports multiple models including Google's Gemini and Anthropic's Claude family (Opus, Sonnet, and Haiku).

Thinking Machines Lab Secures Multi-Billion Dollar Google Cloud Deal for Advanced AI Infrastructure

Mira Murati's startup Thinking Machines Lab has signed a multi-billion-dollar agreement with Google Cloud for access to advanced AI infrastructure, including systems powered by Nvidia's latest GB300 GPUs. The deal supports the company's reinforcement learning workloads for Tinker, a tool that automates the creation of custom frontier AI models, and marks Google's strategy to lock in emerging AI labs early. Thinking Machines previously raised $2 billion at a $12 billion valuation and this represents its first major cloud provider partnership.

See More AI News

AI News Calendar

January 2025
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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.