Chinese Scientists Develop AI-Newton, an AI System Capable of Discovering Physical Laws
A team of researchers in China has created AI-Newton, an artificial intelligence system able to autonomously infer core physical laws directly from experimental data. The breakthrough suggests that AI systems may soon assist or even accelerate scientific discovery without requiring explicit human programming.AI That Mimics the Human Scientific Process
According to the developers, AI-Newton is designed to imitate the way human scientists build knowledge. After receiving raw experimental input, the system gradually forms its own internal library of physical concepts and relationships. This allows it to uncover patterns and formulate symbolic expressions much like a physicist would when analyzing data in a laboratory.Reconstructing Fundamental Laws, Including Newton’s Second Law
The team demonstrated that AI-Newton can derive essential principles such as Newton’s second law of motion, identifying the relationship between force, mass, and acceleration from data alone. It does so without prior instruction or embedded equations, relying instead on its ability to detect structure and consistency within the experimental results.Potential for Autonomous Scientific Breakthroughs
Yang-Qing Ma, a physicist at Peking University, stated that this capability could enable new scientific discoveries made independently by machines. If AI systems can construct conceptual frameworks and infer governing laws, they may eventually propose theories or interpretations that humans have not yet considered.A New Frontier for AI in Research
The development of AI-Newton represents a growing trend in scientific machine learning, where models shift from passive data analysis to active hypothesis generation. As researchers refine these systems, AI could become an increasingly essential partner in physics, chemistry, and other fundamental sciences.Editorial Team — CoinBotLab