On December 10, a significant shift is taking place in the role of artificial intelligence (AI) within scientific research. The "AI-Newton" system, crafted by the team from the School of Physics at Peking University, has showcased remarkable capabilities in autonomous theoretical construction. It has the ability to independently deduce classical mechanics laws from experimental data, encompassing Newton's Second Law, the Law of Conservation of Energy, and the Law of Universal Gravitation.

This groundbreaking accomplishment, which has been published in the prestigious journal Nature, signifies a pivotal transition for AI. It is moving from being merely a supportive tool in scientific research to becoming an "independently cognitive scientific research entity." In an impressive feat, the system autonomously uncovers physical laws by scrutinizing raw experimental data, all without any human oversight or pre-existing physical knowledge. This highlights its formidable capacity for knowledge discovery.

The system's core strength lies in its emulation of the cognitive processes employed by human scientists. It utilizes a "concept-driven knowledge base" and a "plausible reasoning workflow" to incrementally build concepts and laws. Through this methodical approach, it ultimately constructs scientific theories.

This breakthrough not only introduces a novel tool for delving into uncharted scientific territories but also offers invaluable insights for the pursuit of artificial general intelligence.