Cyborg AI Minds programmed to think in memory of the hundreds of murdered Chinese Tiananmen June 4th demonstrators are a true concept-based artificial intelligence with natural language understanding, simple at first and lacking robot embodiment, and expandable all the way to human-level intelligence and beyond. Privacy policy: Third parties advertising here may place and read cookies on your browser; and may use web beacons to collect information as a result of ads displayed here.

Sunday, September 22, 2019

jmpj0922

JavaScript AgiMind understands and thinks with prepositions.

[2019-09-20] In the JavaScript AgiMind.html we are now trying to reproduce the new AGI functionality that we achieved a month ago in the ghost.pl Perlmind. The Ghost in the Machine became able to understand an input like "John writes books for money" and was able to respond properly to a query like "What does John write?"

When we enter "john writes books for money" and the AgiMind responds "WHAT ARE JOHN", it simply means that we need to add the noun "JOHN" to the innate vocabulary. So from the "perlmind.txt" we transfer "JOHN" as concept #504 into the JavaScript free AI source code, and now the AgiMind responds "STUDENTS READ BOOKS", which indicates that the AgiMind knows who or what John is, and what books are. But we also check the Diagnostic mode to make sure that the conceptual associative tags are being assigned properly. We are not sure, so we enter "what does john write" and we get a long response of nonsense.

[2019-09-21] In our second day, we discover that the ReEntry() module has been causing a reduplication of the output of the AgiMind. For troubleshooting, we temporarily disable the ReEntry module. Then we discover that some wrong associative tags are being assigned during human input. We run the ghost.pl AI to see how the correct associative tags are supposed to be assigned.

We discover that a line of InStantiate() code is assigning a false psi19 tpr value when only a zero value should be assigned. The false value being assigned is actually already there, so some other line of code must be assigning it earlier. But there is no earlier assignment, so the false tpr value is obviously being assigned retroactively -- which is something that any AI mind maintainer must learn to watch out for. Probably the retroactive assignment is happening in the EnParser() module, which does a lot of retroactive assignments because one word of human input may have an effect upon an earlier word of human input. Through substitution of "777" as a spurious value in the psi19 location of a snippet of assignment code in the EnParser() module, we discover which snippet is making the erroneous, non-777 assignment. Then through further substitution of "444" in the psi19 slot, we discover an earlier snippet of EnParser() code which is assigning a wrong value at the tvb time-of-verb time-point. So there must be an even earlier "tvb" snippet that is creating a spurious psi19 value. We discover that earlier snippet in the InStantiate() module. After much other coding, when we bring in a reset of tult to zero from the ghost.pl AI, we stop getting the spurious psi19 values.

[2019-09-22] In our third day, we run the ghost.pl AI that already works with prepositional phrases, and we discover that yesterday we trying to fix something that was not even a bug. The AgiMind was properly assigning the tpr tag to link the noun "BOOKS" to the preposition "FOR", and we mistakenly thought that the tag was supposed to be assigned also with "FOR". No, the preposition "FOR" needs only a tkb tag leading to "MONEY" as its object. Now we have gotten the tkb tag to be assigned properly for remembering the object of a preposition. After extensive debugging, we obtain the following exchange:

AI Mind version 22sep19A on Sun Sep 22 19:55:56 PDT 2019
Robot: I UNDERSTAND YOU
Human: john writes books for money

Robot: STUDENTS READ BOOKS
Human:

Robot:
Human: what does john write

Robot: JOHN WRITES BOOKS FOR MONEY