INFERENCE-TIME SCALING AND COLLECTIVE INTELLIGENCE FOR FRONTIER AI

Summary from the TLDR AI newsletter

The new inference-time scaling method combines o4-mini, Gemini-2.5-Pro, and DeepSeek-R1 to achieve 30% on ARC-AGI-2 benchmark, outperforming individual models by dynamically selecting which AI handles each problem. The approach extends Monte Carlo Tree Search to balance generating new solutions versus refining existing ones, with the open-source TreeQuest framework enabling practical deployment.