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Monthly Archives: February 2018

We now accept that raw and uninterpreted perception is an underived truth, one which does not need to be justified or proven. If I see the color green, whether something in my field of view is actually green or even if I’m just hallucinating, I can still accurately state I am perceiving green – even if I don’t know why it is happening, even if no one else is.

We have a pile of raw perceptions, what do we do with it?

We try to “make sense” of this mass of information – by looking for patterns.

Now we have to take a small step back, in order to take a GIANT leap forward: we need to talk a little about patterns.

Check out the following sentences:

  • Eree’t sitttina dpomsssfr aie nnee retmr, aemaothdr etmnh ose et.
  • Ir oimtn attsfroee nrs setnmmern ehreapid, hese eat omte’a tdste.
  • Hrn mdsa eeas’e tentteimi setatntee itr, doftr opehrmso snmra ee.
  • Hent ttnerfemm si dsdohmnia noees srti’a, etesr apmeereo ttr tea.
  • Reo enne eoea’i eed et mrmes, hadhtttie trstpmes srtimntna rfoas.

Total gibberish, right? This is an analogy for what uninterpreted sense data is like – sure, it’s data, but it doesn’t mean anything to us.

Imagine for a moment that you don’t know how to read or write at all, that you didn’t know the alphabet, nothing. Then the following sentence would be as much gibberish as the five above:

  • Sometimes there are patterns to find, and sometimes there aren’t.

Here’s the thing: all six sentences (the first five and the one directly above) use exactly the same specific letters and have the same exact number of words, each word with the same number of letters. The only difference is the way the letters and the words are ordered.

That sixth sentence is as unintelligible to an illiterate person as the first five were to you – an illiterate person cannot see a difference among any of the six sentences, and they certainly would be at a total loss to say them aloud, let alone glean any iota of understanding.

But once we’ve have learned the code, the way to find the pattern, we can easily not only read the sixth one out loud, but understand perfectly what message it is trying to convey!

Learning patterns is the key to understanding that what might seem like random noisy data may actually hide meaning and truth – we just first have to learn how to decrypt it.

So how do we do that? How do we find meaningful patterns in our raw perceptions?

That, my friends, is the meat of the matter, which is next.