Laws in Maths & Physics emerge from the engineering of AI models.

For example in Deep Neural Networks, the model will optimize and exploit the data to find the most efficient way to generalize or predict just like every system in nature finding the least path of resistance.

It’s almost like AI models simulate the universe’s logic. Other examples are how Gradient descents behave like entropy in reverse or Regularization mimics constraints found in natural systems or how Generalization is akin to harmony, where structure meets flexibility.

When engineering the architecture of Deep Neural Networks, are we discovering laws of thought or rediscovering the thought of laws?

Can observing AI models and how it interacts with other technologies reveal new laws of Maths & Physics applicable to our physical reality?

WATTBA