Neural Networks and Rules-based Systems used to find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions

Abstract

What you will read in the next pages is truly an anthology-worthy element, in the sense that it is to be taken seriously; in fact, the place that we will try to describe in this work, in the sense of arriving in an unknown place, which therefore will not be easy to describe. In the path that takes us from non-existence to being and becoming... placed in this location, it becomes interesting that different things or people coexist that have not yet been presented in the era in which we connect and go to browse. A very important aspect is the determination of the window in which one says he had a dream where he saw a car that does not yet exist today but perhaps will exist in the future, or a deceased person or one who will exist in the future; So, once the time window is set, which isn't easy, and determining it is an important aspect in which brainwaves will then be selected. This selection is easy and precise when you're awake and thinking about something and the time window is very clear, so a small interaction with the person is enough. It's a different story when you're dreaming. Shannon's theorem, used in electrical engineering and telecommunications, helps select and "correlate" signals. Why this theorem was invented, crucial for effectively sampling signals and being able to fully reconstruct them, is one of those mysteries that leads us to ask ourselves at lunch with the family: Do I have a colleague?

We must therefore perfect the start and stop of recording during the dream by focusing on where we are interested, useful for discovering what we think and that our brain suggests things that we thought were lost in our historical culture and instead suddenly... what we need emerges.

We would therefore try to obtain feedback from Afterlife in order to reproduce the brain waves seen in the dream phase thanks to a helmet connected to proactive and not just generative Artificial Intelligence.