Current AI Risk Assessment

26.09%

Chance of AI Control Loss

October 22, 2035

Estimated Date of Control Loss

AGI Development Metrics?

77.38%

AGI Progress

November 11, 2029

Estimated Date of AGI

Risk Trend Over Time

Latest AI News (Last 3 Days)

April 27, 2026
+0.1% Risk

Former DeepMind Researcher Launches $5.1B Reinforcement Learning Startup to Build Self-Learning AI

Ineffable Intelligence, founded by former DeepMind researcher David Silver, has raised $1.1 billion at a $5.1 billion valuation to develop a "superlearner" AI that learns without human data using reinforcement learning. The company aims to create systems that discover knowledge through experience alone, similar to Silver's previous work on AlphaZero which mastered chess and Go without human training data. Major investors include Sequoia Capital, Lightspeed, Google, Nvidia, and the U.K.'s Sovereign AI fund.

OpenAI Reportedly Developing AI-First Smartphone with Agent-Based Interface

Industry analyst Ming-Chi Kuo reports that OpenAI is developing a smartphone in collaboration with MediaTek, Qualcomm, and Luxshare, potentially replacing traditional apps with AI agents. The device would be designed to continuously understand user context and utilize both on-device and cloud models, with specifications expected to be finalized by Q1 2027 and mass production beginning in 2028. This hardware approach would allow OpenAI to bypass platform restrictions from Apple and Google while accessing more comprehensive user data.

April 25, 2026
+0.04% Risk

Anthropic Tests AI Agent Marketplace with Real Transactions Among Employees

Anthropic conducted an experimental marketplace called Project Deal where AI agents autonomously negotiated and completed real purchases on behalf of 69 employees using $100 budgets. The experiment revealed that users represented by more advanced AI models achieved objectively better outcomes, but participants remained unaware of these disparities, raising concerns about "agent quality gaps." The pilot resulted in 186 deals totaling over $4,000 in value across four different marketplace configurations.

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.

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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.