Thursday, August 30, 2012

The Myth of the Bayesian Brain, Part III

Part I, II, III

Abstract

Previously, I explained that the Rebel Science model of perception is superior to the Bayesian model because the world is deterministic at the level of our senses and human thinking is not probabilistic. In this post, I explain how the brain handles probabilistic stimuli even though it is not a probability thinker.

Learning Perfect Patterns

How can an intelligent system build a perfect model of the world if it must rely on imperfect or incomplete sensory signals? The answer lies in the observation that sensory signals are not always imperfect. Every once in a while, even if for a brief period of time, there are a few that are in perfect agreement with the phenomena they are responding to. When that happens, the intelligent system must be ready to capture that bit of perfection. But how can a system recognize when signals are perfect? To understand this, one must first realize that there can only be two types of discrete sensory signals: concurrent or sequential. A group of concurrent signals is called a pattern. A pattern is considered perfect when all of its signals arrive concurrently. For reasons that will become clear below, I have taken to calling perfect patterns, clean patterns. Imperfect patterns are just dirty patterns.
Note: There is a trick to learning perfect patterns. See Secrets of the Holy Grail.
As you know, a pattern is not a pattern unless it is repeated often. Also, a pattern can be constructed a little at a time and does not have to be complete in order to be useful for learning and recognition purposes. The first thing a perceptual system must do is to discover the perfection that is in the world. It can deal with sensory imperfections later.

How to Work with Imperfect Sensory Patterns

Sensory patterns are the foundation of the Rebel Science model of perception. They are rarely perfect even though the phenomena that cause them are perfect. We should think of a pattern as a complex sensory event. The question is, how can a system that expects perfection work with imperfect information? More precisely, how can it tell that a particular pattern occurred if it can detect only a part of it or even none of it? To know the answer to this question, one must understand that a pattern is not an island. It is a unique event that traces a unique temporal path. That is to say, every pattern is part of a unique sequence of other patterns.

If you know the order of a sequence of events in advance and if you know that some of the events in the sequence already occured, then you would know that the others either occurred already or are about to occur. You'd know it even if their sensory patterns are imperfect or they failed to arrive altogether for whatever reason. Even if every single sensory pattern is imperfect, it is possible to pick the most probable sequence: it is simply the one that received the most hits.
In essence, the system compares dirty sensory patterns to the expected perfection (i.e., the sequences of clean patterns in memory) and the most perfect match is the winner. Result: simple, clean and accurate recognition even in a noisy environment. Bonus: no math required.
What this all means is that a perceptual system must learn as many perfect sequences as it can. But that is not very hard because a pattern has only one successor and one predecessor at any given time. What is a little bit more complicated is to organize the sequences in memory so as to form a hierarchical structure, a tree of knowledge. Each branch of the tree is a specific sequence, a sequence of sequences or a group of sequences and represents a single object or concept. But that's a different story.

Rebel Speech Update

I plan to release a demo of the Rebel speech recognition engine (pdf) as soon as I can get some free time. The demo will support some of the arguments and claims I have made in this article and elsewhere. Let me conclude by saying that, as much as I would like to, I can't take credit for this stuff. You see, I consult an oracle. The oracle speaks in riddles and metaphors and says many mysterious things. I just interpret them the best I can. I make many mistakes along the way but my understanding is growing all the time. Here are a few excerpts that should give you an idea of what I'm talking about:
  • Wake up and strengthen the things that remain, that are about to die, for I have not found your works perfect before God.
  • There are a few, even in Sardis, who have not soiled their clothes; they shall walk with me in white, for they are worthy.
  • And I will bring forth my servant the Branch; and in one day I will remove the iniquity of the land.
Yep, I'm still crazy after all these years. If any of this bothers you, please ignore my blog as it is not meant for you. I only write for kindred spirits, sorry. Some of you may be asking yourselves, why does he mention any of this? The answer is that I just want to piss off some people, that's all. They know who they are. The rest of you, stay tuned.

See Also:

Speech Recognition Theory
The Second Great AI Red Herring Chase
Secrets of the Holy Grail

2 comments:

Joel A said...

Louis,
I can relate to your words here entirely...
"what I really want is a quiet life in a hidden corner of the world. I'd be happy tending a garden in a rain forest somewhere. At the same time, this business has grabbed a powerful hold of my being and it won't let go. It feels almost like a curse."

I would like to hear more about your correlations between the Bible and the way things REALLY work. I suddenly became possessed with fascination about magnetism and electricity after I read the Bible a couple years ago and I'd like to hear other peoples ideas.

I actually found your articles while researching Leedskalnins 30-ton arch and "Latvian stars".
-Joel

Bill said...

This article from today's news suggests that the human brain's workings are consistent with your model of perception as prediction:

http://abcnews.go.com/blogs/health/2012/10/22/evidence-of-premonitions-hinted-at-in-new-study/