Source: thenewstack.io
Machine Learning Algorithm Sidesteps the Scientific MethodCategory: machine-learning, artificial-intelligence
The scientific method — based on the process of observation, formulating a hypothesis, then going through experiments to either prove or disprove that hypothesis — has been the cornerstone of modern science for several centuries. It’s a technique used by many scientific fields, as it provides a structured guideline to answering a question logically and rationally, using empirical evidence — an approach that ushered humanity out of the dark ages and into today’s era where breakthrough discoveries in physics, astronomy and modern medicine are possible.
They explain: “The laws of physics are fundamentally expressed in the form of field theories instead of differential equations.
In the field of physics, however, machine learning algorithms are typically used to model complex processes like plasma disruptions in magnetic fusion devices, or modeling the dynamic motions of fluids.
The algorithms developed are robust against variations of the governing laws of physics because the method does not require any knowledge of the laws of physics other than the fundamental assumption that the governing laws are field theories,” said the team.
They explain: “The laws of physics are fundamentally expressed in the form of field theories instead of differential equations.
In the field of physics, however, machine learning algorithms are typically used to model complex processes like plasma disruptions in magnetic fusion devices, or modeling the dynamic motions of fluids.
The algorithms developed are robust against variations of the governing laws of physics because the method does not require any knowledge of the laws of physics other than the fundamental assumption that the governing laws are field theories,” said the team.
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