Aug
31
2011
Human languages allow us to very concisely and accurately talk about things. Although at some levels talk involves ambiguity (many meanings are possible for the words and phrases used) our ability to discuss complex ideas quickly stems from the fact that talk conveys meaning, not mere words.
Our prototype that resulted from project Turing demonstrates how simple patterns can quickly result in very complex meanings. The hierarchy is the key here – by matching patterns in a hierarchy, higher level patterns rapidly take on meaning which as a single level would be complex.
The video today shows how a word can take on many shapes. Whether it is a list of symbols, like in a number, or of characters as in English words or unbroken strings of characters as in Japanese sentences, meaning comes from the same elements of a sentence. Unfortunately for the programmers of the past trying to match these patterns, the pieces that fit into a sentence are quite varied, as varied as the words that make up a language.
The application of Patom theory does away with a number of issues that plagued programmers in the past. The computer finds the atoms that make up a word, based on its current use, and then seeks to apply it to the current sentence.
To try to make this clearer, a word is something that describes a particular idea. So the number “40” represents the concept of forty things. The phrase “John, Beth and Sue” is a word that describes 3 people. And the phrase “ruthere” which reads “are you there” is a question, a full sentence when you expand it out.
We think that the approach of bundling phrases into words on the fly and ensuring it fits into a sentence is a good way to comprehend real languages - as we want to do.