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  /  Project   /  Blog: Mens Latina — 2019–04–24

Blog: Mens Latina — 2019–04–24


Rushing in medias res we grapple today with one of the most difficult problems in either a Latin AI or a Russian AI, namely, how to generate missing verb forms when there are four different conjugations of verbs. Our English AI Minds have hardly any inflections at all on English verbs in the present tense. Our German AI must deal with fully inflected German verbs, but with only one standard conjugation. Therefore in English or in German it is easy to use a standard paradigm of verb-forms to generate a missing verb-form. In Latin or in Russian, the verb-generating mind-module must contain the data for handling missing forms in compliance with the paradigm of the conjugation of the target verb.

Today we start by fleshing out the PraeScium MindBoot sequence with the infinitive forms of “amare” (“to love”) in the first Latin conjugation; “habere” (“to have”) in the second conjugation; and “audire” (“to hear”) in the fourth conjugation. We alread have “mittere” (“to send”) in the third conjugation. We also insert the substantive plural noun “QUALIA” (“things with qualities”) just so we will have a direct object to use with any of the four Latin verb conjugations. We are keenly aware of “qualia” as one of the most hotly debated topics in the broad field of artificial intelligence. We Latin classicists own that topic of “qualia”, and so we exercise our privilege of bandying the word about. In fact, we type in “tu mittis qualia” and the Latin AI eventually answers us in perfect Latin, “EGO MITTO QUALIA”.

But we know that we have only “kludged” together the ability of the Latin AI to convert “mittis” to “mitto”. (Pardon my geek-speak.) We made the LaVerbGen module able to deal with “mittis” as if there were only one Latin conjugation of verbs, to verify the proof-of-concept. Now we need to implement an ability of LaVerbGen in Latin or RuVerbGen in Russian to deal with multiple verb-conjugations. Perhaps coding an AI in Latin is yielding a major dividend for our AI work in Russian, which we had been neglecting in the ghost.pl AI in Perl while we concentrated on inculcating (no?) or implementing advanced mental feautures in English. If we solve the problem in ancient Latin, we will rush to implement it also in modern-day Russian. Now let us look at the problem.

Currently a mentifex-class AI Mind uses the audbase variable as a base-point or starting-point in auditory memory for an example of the target-verb which must be converted from an available form to a missing form. In English or in German, any example of a regular verb will provide for us the stem of the verb, upon which we can build any desired present-tense verb-ending, as in “Verstehst du?” (“Do you understand?”) in German. In Latin or Russian, though, the audbase is not enough. It may give us the stem of the generand verb, but we also need to know what kind (conjugation) of verb we are dealing with. (Since anyone reading this text is probably a classicist, we will make up words like “generand” whenever we need them, okay? Strictly on a “need-to-know” basis, right? And does anybody object to providing in Latin what could be the key to world-wide AI dominance in Russian?)

This problem is a very difficult problem in our monoglot or polyglot AI. As we solve the problem for present-tense Latin verbs, we must exercise due diligence in not choosing a solution that will interfere with other Latin verbs in the future tense or in the subjunctive mood. For example, we can not say that “mittas” is obviously a first-conjugation Latin verb, when truly it is a third-conjugation verb in the subjunctive mood. If the problem proves insoluble or at least intractable, we may have to give up on generating Latin verb-forms and let each computer learn Latin by a trial-and-error method, the way Roman children did two thousand years ago.

We can not simply look at the infinitive form to determine which paradigm a Latin verb should follow, because verbs like “habere” and “mittere” look very similar in the infinitive. We may have to rely upon two or three clues for our selection of the correct Latin paradigm. We could set up an algorithm which does indeed look for the infinitve form, to see if it exists in memory and if it is recognisably first-conjugation or fourth-conjugation. Then in a secondary approach we could have our AI look for various branches beyond the infinitive clue. If we definitely have an “-ere” infinitive like for second-conjugation “habere” or third-conjugation “mittere”, we could look for an inflection containing “E” to suggest second conjugation or containing “I” to suggest third conjugation. Those two clues put together, based on both infinitive and inflectional ending, are still not enough to prevent “mittes” in the future tense from being interpreted as a second-conjugation verb in the present tense, like “habes”. In the ancient Roman mind, the common verb-forms were probalby so well known that the speaker of Latin could find any desired form already in memory and did not need to generate a verb-form on the fly.

So perhpas we should be satisfied at first with a fallible algorithm. We can implement a package of tests and include it in the AI Mind, even though we know that further evolution of the AI will require further evolution of the package of conjugation-tests. And these tests may be more problematical in Latin than they are in Russian, so our makeshift solution in Latin may actually be a very solid solution in Russian.

So let us set up a jug variable to keep track of which conjugation we think we are dealing with.

Source: Artificial Intelligence on Medium

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