Jul 30, 2026 · Artificial Intelligence

OpenAI Finds Two Settings Triple ARC‑AGI‑3 Scores—Agent Memory, Not Model, Drives Gains

OpenAI shows that enabling retained reasoning and context compaction boosts ARC‑AGI‑3 performance from 13.3% to 38.3% (about three‑fold) by preserving the agent’s working memory, a finding that reshapes how we evaluate and design AI agents beyond raw model weights.

AI agent designARC-AGI-3Agent Memory

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OpenAI Finds Two Settings Triple ARC‑AGI‑3 Scores—Agent Memory, Not Model, Drives Gains

Machine Heart

Jul 18, 2026 · Artificial Intelligence

How the [schema] Harness Achieved 99% RHAE on ARC‑AGI‑3 by Making AI Think Like a Physicist

The article explains how the [schema] harness, a lightweight framework that wraps large language models, transformed ARC‑AGI‑3 scores from sub‑10% to 98.98% by grounding observations into state representations, discovering mechanisms, and iteratively testing hypotheses, while also discussing the benchmark’s scoring rules, potential “cheating” concerns, and the broader implications for AI research.

AI benchmarkingARC-AGI-3LLM

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How the [schema] Harness Achieved 99% RHAE on ARC‑AGI‑3 by Making AI Think Like a Physicist