Is there any new scientific capability to build non-causal filters in real world?
is there any new scientific theory which could yield to making none causal FIR Filters in the real world?


No. If anything, scientific theories seem to be challenging determinism itself, which is what could allow you to peer ahead in the future. The key here is the last phrase of that quote ("...many times the signal is stored and then processed...").

If you already had acces to the true $x[n+1]$ at the level of observation of a signal, why not use a causal filter anyway? What is so special about $x[n+1]$?

For instance, take a very simple finite difference filter. You can definitely express it as:

$$ y[n] = x[n+1] - x[n]$$

But you would not be able to apply it in real time. The objective here is to take the difference between two samples. If you wait for $x[n+1]$ to happen, you can simply:

$$ y[n] = x[n] - x[n-1]$$

If it was possible for this difference to work in the presence of $x[n+k]$, then $y$ could start producing some output before $x$ even begins to occur.

You can observe exactly what this would sound like in a time reversed reverb. Here is an example of that.

To try this yourself, load a sound in Audacity, apply "Reverse", "Reverb" and finally "Reverse" again, before hitting "Play".

In reverberation, present samples bear some resemblance to past samples. If you stand at the far end of a large room, sounds from sources with a direct line-of-sight to your ears reach you much faster than sounds that have to bounce off of the walls. The sounds that bounce off of the walls travel a longer distance and therefore reach you later. This is what is causing the time difference of different reflections in reverberation.

By reversing the sound clip, you make the current sample to bear resemblance to its future values, thus starting to hear reflections of an event that has not yet happen.

This is only possible with signals that are stored.

Hope this helps.