Imagine a four-core, 64-bit Forth AI CPU designed to run a not-quite-
maspar but still somewhat parallel artificial intelligence in English http://www.scn.org/~mentifex/mindforth.txt or in http://www.scn.org/~mentifex/DeKi.txt German.

Such a specialized, Strong AI Forth CPU could devote one core to visual processing and memory; a second core to auditory input and memory; a third core to robotic motor memory and output; and a fourth core to automated reasoning with http://code.google.com/p/mindforth/wiki/InFerence in English, German or Russian.

The 64-bit Forth CPU could be architecturally simple by dint of leaving out all the customary circuitry used for floating-point arithmetic, and Forth would serve as its own AI operating system.

JavaScript Artificial Intelligence Programming Journal

In the English JSAI (JavaScript artificial intelligence), the "nounlock" variable holds onto the time-point of the direct object or predicate nominative for a specific verb. Since the auditory engram being fetched is already in the proper case, there may not be any need to specify any parameters during the search.

As we run the English JSAI at length without human input and with the inclusion of diagnostic "alert" messages, we discover that the JSAI is sending a positive "dirobj" flag into NounPhrase without checking first for a positive "predflag".

Yesterday we commented out NounPhrase code which was supposed to "make sure of agreement; 18may2011" but which was doing more harm than good. The code was causing the AI to send the wrong form of the self-concept "701=I" into the SpeechAct module. Now we can comment out our diagnostic "alert" messages and see if the free AI source code is stable enough for an upload to the Web. Yes, it is.

German Artificial Intelligence Programming Journal

In the German Wotan artificial intelligence with machine reasoning by inference, the AskUser module converts an otherwise silent inference into a yes-or-no question seeking confirmation of the inference with a yes-answer or refutation of the inference with a no-answer. Prior to confirmation or refutation, the conceptual engrams of the question are a mere proposition for consideration by the human user. When the user enters the answer, the KbRetro module must either establish associative tags from subject to verb to direct object in the case of a yes-answer, or disrupt the same tags with the insertion of a negational concept of "NICHT" for the idea known as "NOT" in English.

Although the AskUser module is asking the proper question, "HAT EVA EIN KIND" in German for "Does Eva have a child?", the concepts of the question are not being stored properly in the Psi conceptual array.

Now we have coordinated the operation of InFerence, AskUser and KbRetro. When we input, "eva ist eine frau" for "Eva is a woman," the German AI makes a silent inference that Eva may perhaps have a child. AskUser outputs the question, "HAT EVA EIN KIND" for "Does Eva have a child?" When we answer "nein" in German for English "no", the KbRetro module adjusts the knowledge base (KB) retroactively by negating the verb "HAT" and the German AI says, "EVA HAT NICHT EIN KIND", or "Eva does not have a child" in English.

When the German Wotan AI uses the InFerence module to think rationally, the AI Mind creates a silent, conceptual inference and then calls the AskUser module to seek confirmation or refutation of the inference. While generating its output, the AskUser module calls the DeArticle module to insert a definite or indefinite article into the question being asked. The AI has been using the wrong article with "HAT EVA DAS KIND?" when it should be asking, "HAT EVA EIN KIND?" When we tweak the software to switch from the definite article to the indefinite article, the AI gets the gender wrong with "HAT EVA EINE KIND?"

In the AskUser module, to put a German article before the direct object of the query, we may have to move the DeArticle call into the backwards search for the query-object (quobj), so that the gender of the query-object can be found and sent as a parameter into the DeArticle module.

It may seem like a radical departure to call DeArticle from inside the search-loop for a noun, but only one engram of the German noun will be retrieved, and so there should be no problem with inserting a German article at the same time. The necessary parameters are right there at the time-point from which the noun is being retrieved.

When the OldConcept module recognizes a known German noun, normally the "mfn" gender of that noun is detected and stored once again as a fresh conceptual engram for that noun. However, today we have learned that in OldConcept we must store a zero value for the recognition of forms of "EIN" as the German indefinite article, because the word "EIN" has no intrinsic gender and only acquires the gender of its associated noun. When we insert the corrective code into the OldConcept module, finally we witness the German Wotan AI engaging in rational thought by means of inference when we input "eva ist eine frau", or "Eva is a woman." The German AI makes a silent inference about Eva and calls the AskUser module to ask us users, "HAT EVA EIN KIND", which means in English, "Does Eva have a child?" Next we must work on KbRetro to positively confirm or negatively adjust the knowledge base in accordance with the answer to the question.

As we implement InFerence in the Wotan German Supercomputer AI, the program tends to call the WhatBe module to ask a question about a previously unknown word. When we input to the AI, "eva ist eine frau", first Wotan makes an inference about Eva and asks if Eva has a child. Then the AI mistakenly says, "WAS IRRTUM EVA" when the correct output should be "WAS IST EVA". This problem affords us an opportunity to improve the German performance of the WhatBe module which came into the German AI from the English MindForth AI.

First we need to determine which location in the AI source code is calling the WhatBe mind-module, and so we insert some diagnostics. Knowing where the call comes from, lets us work on the proper preparation of parameters from outside WhatBe to be used inside WhatBe.

We are learning that we must handle grammatical number much differently in the German AI than in the English AI. English generally uses the ending "-s" to indicate plural number, but in German there is no one such simple clue. In German we have a plethora of clues about number, and we can use the OutBuffer to work with some of them, such as "-heit" indicating singular and "-heiten" indicating plural. In German we can also establish priority among rules, such as letting an "-e" ending in the OutBuffer suggest a plural noun, while letting the discovery of a singular verb overrule the suggestion that a noun is in the plural. The main point here is that in German we must get away from the simplistic English rules about number.

In NewConcept let us try changing the default expectation of number for a new noun from plural to singular. At first we notice no problem with a default singular. Then we notice that the InFerence module is using a default plural ("2") for the subject-noun of the silent inference. We tentatively change the default to singular ("1") until we can devise a more robust determinant of number in InFerence.

We are having a problem with the "ocn" variable for "old concept number". Just as with the obsolete "recnum", there is no reason any more to use the "ocn" variable, so we comment out some code.