Hong Qin algorithm can question everything we know about reality, and whether everything is a simulation or not.
There are ongoing theories that talk about artificial stimulation arguing that what we experience as reality is actually a giant computer stimulus created by a more sophisticated intelligence.
Hong, from the Physics Laboratory in Princeton, USA, invented an algorithm to predict the orbits of the planets and implemented it in the orbits of Mercury, Venus, Earth, Mars and Jupiter. He is now developing Artificial Intelligence so that he can potentially predict and control other behaviors.
The physicist explains:
"Usually in physics, you make observations, you create a theory based on those observations, and then you use that theory to predict new observations. What I'm doing is replacing this process with some kind of black box that can "produce accurate predictions without using a traditional theory or law. I basically skipped all the basic components of physics and went straight from some data to some others."
Hong taught a program the basic principle used by nature to determine the dynamics of any physical system. The reward is that the network learns the laws of planetary motion after seeing very few examples of training. In other words, his code really "teaches" the laws of physics. He is now trying to adapt the algorithm to predict other natural phenomena.
The professor is said to have been inspired in part by the experiment of philosophical thought of Nick Bostrom, the Oxford philosopher, who argues that the universe can be an artificial stimulus.
What is the algorithm that works on the universe laptop? If such an algorithm exists, I would argue that it should be a simple algorithm defined in the discrete time space grid. The complexity and wealth of the universe come from the large size of memory and the power of the laptop CPU, but the algorithm itself can be simple.
There are still many questions and other discoveries to be made, but Hong is convinced that more findings are expected in the future.
If you follow stimulus theories, this video might interest you:
Source: Big Think, Unilad,
