Sean Hendryx

AI superintelligence will require learning environments that mirror how humans achieve breakthroughs: combining verifiable rewards with collaborative interaction. New research from Scale demonstrates this principle in action. By creating a "student-teacher" framework where an AI receives targeted, natural language guidance when it struggles, researchers significantly accelerated learning and performance in complex reasoning and SWE tasks. This approach, which integrates dynamic feedback with verifiable outcomes, marks a real step toward building more powerful and efficient AI systems.

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