Science courses emphasize the notion of a definitive answer when it comes to certain principles, but professors highlight that science is an ever-changing field. This change can be seen in biology, chemistry and physics. 

Contrary to the typical view as a tool for cheating in the physics field, physicists from Emory University found a way to use artificial intelligence to develop physics. 

This was done by using neural network models and dusty plasma: a substance that has suspended gas particles in ionized gases. 

This led physicists to discover the interaction between dusty plasma and non-reciprocal forces, where particles push against another in distinct ways.

This notion differs from past theories of physics. Hence, AI as a tool may be viewed as another physicist. Justin Burton, physics professor at Emory University and part of the research team indicates AI will expand governments and our understanding of physics.

The significance of the Emory physicists’ discovery is that it opens a multitude of understanding other body systems, unlocks previously unknown areas of physics and allows us to gain a better grasp of natural physics.

How did the experimental physicists decide this was the best way to test plasma? The answer lies in how AI articulates physical properties on a deeper level. 

As noted in peer-reviewed journal The Proceedings of the National Academy of Sciences, AI models have better force equation calculations and validations. 

AI has a better handle on tweaking experimental setups in terms of density and size. 

Physics is the father of all sciences. If physics can use the AI method of dusty plasma within many of its subfields, there is no reason why this advancement can’t help with chemistry and even the biological sciences.

This advancement can help in the field of chemistry by providing a better understanding of chemical reactions and molecule swarms. 

Illinois experts found a more specific application in refined control. As dusty plasma breeds nanoparticles — which are used as semiconductors found in light sources like LED lights in teenage bedrooms or to fight contamination in chip-making — AI can accurately predict growth rates and clumping. 

This understanding will help create better products with innovative and engineer-able progressions. 

This is beneficial in chemistry field as the focus shifts to the biological applications of these methods. Specifically understanding cellular systems ties into the other system application part of the AI method, which will find rules from messy motion data that can not be interpreted by human investigation.

This could lead to advancements in cancer research through finding out the rules governing the origin and progression of cancer, in part by understanding the tugs between cellular tissues, like how dusty plasma tugs are on particles. 

The AI method can fill in the blanks of human research. 

From that research, a product or advancement can be produced to better humans. Almost any scientific discovery can be correlated to the practice of medicine.

From ancient Egyptians using the forces of nature to engineer inclined planes, to now naming the physics governing the notion of this innovation, AI has returned the favor and allowed for further innovations to be made. Innovation is built on intelligence and science, without which society wouldn’t be where it is today.