Beyond GPT: Evolutionary Algorithm Conquers ARC-AGI, Hints at AGI?

A researcher recently achieved a significant breakthrough in the ARC-AGI benchmark using an evolutionary algorithm combined with the large language model Grok-4. The approach achieved 79.6% accuracy on ARC v1 and a state-of-the-art 29.4% on the harder ARC v2. The core innovation lies in using natural language instructions instead of Python code, iteratively evolving to generate more effective solutions. This research suggests that combining reinforcement learning and natural language instructions could address the limitations of current LLMs in abstract reasoning, paving the way for Artificial General Intelligence (AGI).