Two languages,Sanskrit and Tamil are the oldest languages of Humanity.
While Tamil is in very much vogue, spoken Sanskrit is practically dead, save in a few villages in Maharashtra near Pune and in Kerala.
Both the languages though unique in their own way, they have influenced each other.
One of the reasons for these languages being called Rich is the fact that they are as logical as Mathematics and Logical Positivism.
Language to be rich should have the capacity to transmit thoughts unambiguously, logically the Human feelings and emotions.
This can be achieved in two primary ways.
One is that one word indicating a thing or feeling shoudl have as many words as possible to differentiate and convey the exact feeling or thought.
Tamil achieves this by possessing as many word as possible to indicate the same thing or feeling.
For instance, the word which one uses for” more in Tamil is ‘Athikam/Jaasthi.
These words unfortunately are not Tamil.
There are Seven words to convey the meaning with a slight difference.
They are,
சால, உறு, தவ ,நனி ,கூர் ,கழி, மிகல்.
There is a fine distinction between these words .
This way Tamil makes sue one expresses feelings exactly.
The second is that emotions and thoughts can be expressed through the tone.
This Sanskrit achieves by differentiating sounds.
Letters have different sounds to differentiate sounds.
The sound ‘ka’ as four different tones and this is accommodated in Sanskrit by ascribing four different letters.
Depending on he tone, the meanings change.
And to make things more clear in a Language, clarity has to be achieved by giving prominence to the Verb.
Both Tamil and Sanskrit use this to the maximum advantage.
Computer programming needs such clarity of thought and logical sequencing.
This becomes more critical in Artificial Intelligence.
Sanskrit has been found to be the most suited for developing Artificial Intelligence.
NASA Research papers confirm this.
A Report.
There is at least one language, Sanskrit, which for the duration of almost 1,000 years was a living spoken language with a considerable literature of its own. Besides works of literary value, there was a long philosophical and grammatical tradition that has continued to exist with undiminished vigor until the present century. Among the accomplishments of the grammarians can be reckoned a method for paraphrasing Sanskrit in a manner that is identical not only in essence but in form with current work in Artificial Intelligence. This article demonstrates that a natural language can serve as an artificial language also, and that much work in AI has been reinventing a wheel millenia old.
Semantic Nets
For the sake of comparison, a brief overview of semantic nets will be given, and examples will be included that will be compared to the Indian approach. After early attempts at machine translation (which were based to a large extent on simple dictionary look-up) failed in their effort to teach a computer to understand natural language, work in AI turned to Knowledge Representation.
Since translation is not simply a map from lexical item to lexical item, and since ambiguity is inherent in a large number of utterances, some means is required to encode what the actual meaning of a sentence is. Clearly, there must be a representation of meaning independent of words used. Another problem is the interference of syntax. In some sentences (for example active/passive) syntax is, for all intents and purposes, independent of meaning. Here one would like to eliminate considerations of syntax. In other sentences the syntax contributes to the meaning and here one wishes to extract it.
..
It is obvious that the act of receiving can be interpreted as an action involving a union with Mary’s hand, an enveloping of the ball by Mary’s hand, etc., so that in theory it might be difficult to decide where to stop this process of splitting meanings, or what the semantic primitives are. That the Indians were aware of the problem is evident from the following passage: “The name ‘action’ cannot be applied to the solitary point reached by extreme subdivision.”
The set of actions described in (a) and (b) can be viewed as actions that contribute to the meaning of the total sentence, vix. the fact that the ball is transferred from John to Mary. In this sense they are “auxiliary actions” (Sanskrit kuruku-literally “that which brings about”) that may be isolated as complete actions in their own right for possible further subdivision, but in this particular context are subordinate to the total action of “giving.” These “auxiliary activities” when they become thus subordinated to the main sentence meaning, are represented by case endings affixed to nominals corresponding to the agents of the original auxiliary activity. The Sanskrit language has seven case endings (excluding the vocative), and six of these are definable representations of specific “auxiliary activities.” The seventh, the genitive, represents a set of auxiliary activities that are not defined by the other six. The auxiliary actions are listed as a group of six: Agent, Object, Instrument, Recipient, Point of Departure, Locality. They are the semantic correspondents of the syntactic case endings: nominative, accusative, instrumental, dative, ablative and locative, but these are not in exact equivalence since the same syntactic structure can represent different semantic messages, as will be discussed below. There is a good deal of overlap between the karakas and the case endings, and a few of them, such as Point of Departure, also are used for syntactic information, in this case “because of”. In many instances the relation is best characterized as that of the allo-eme variety..
Citation of the excerpts from.
http://www.vedicsciences.net/articles/sanskrit-nasa.html
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