How the monitored publications were assessed

Discourse valence across every scored item: what the sampled sources published and how independent models read it. It is not a measure of public opinion, not a measure of the state of the world, and article volume is not agreement.

15 items read as favourable

• EvoBelief: Falsifiable World Models for Self-Improving LLM Agents
  +20 arXiv cs.AI 2026-10-12 single model
• AI Solves a Major Unsolved Math Problem. Not Everyone Is Happy
  +20 IEEE Spectrum: AI 2026-10-05 single model
• AREX-2: Advancing Self-Improving Agents through Long-Horizon Reflective Tasks
  +20 arXiv cs.AI 2026-10-01 single model
• Generative AI Gives Spacecraft the Autonomy Engineers Once Feared
  +20 IEEE Spectrum: AI 2026-09-28 single model
• Agentic Economies for Autonomous Scientific Discovery
  +20 arXiv cs.CY (Computers and Society) 2026-09-28 single model
• Google's first Suncatcher orbital data center test launches October 1
  +20 Ars Technica: AI 2026-09-24 single model
• AutoGym: Blueprint-First Generation of Verifiable Agent Gyms
  +20 arXiv cs.AI 2026-09-23 single model
• How GPT-5.6 Sol helps run quantum computing experiments
  +20 OpenAI 2026-09-08 single model
• Self-Evolving Harness on Multiple Tasks with the Agent as Its Own Optimizer
  +24 arXiv cs.AI 2026-10-01 low agreement · ±88
• TACS-RF: Tool-driven Agentic Circuit Synthesis of RF and mmWave Modules
  +27 arXiv cs.AI 13d ago moderate agreement · ±38
• OpenAI claims to have solved maths problem that stumped humans for decades
  +28 The Guardian: Artificial Intelligence 2026-09-08 high agreement · ±15
• DeepMind unveils Genie 4 world model promising more realistic physics and humans
  +50 Ars Technica: AI 12d ago single model
• Solving a 31-year-old grand challenge in mathematics – the KLS conjecture
  +50 Microsoft Research 2026-10-21 single model
• EvolvingBrain: An Adaptive Skill System for Multi-modal Agents Self-Evolution in Open Worlds
  +50 arXiv cs.AI 2026-10-16 single model
• Transformer-Based Masked Diffusion Models Provably Learn Distributions with Latent Structure
  +50 arXiv cs.LG (Machine Learning) 2026-10-12 single model

Across the whole window

The two tables below describe every item in the last 90 days under agi-timelines. They are deliberately not narrowed by the reading filter (currently favourable), because a mean taken only over items already selected for their score would just restate the filter.

By topic

By source

A source's mean says how the items it published were read. It is not a rating of the source.