Remember Tiananmen Massacre

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.

Saturday, May 25, 2019


Converting ancient Latin artificial intelligence into modern Russian AI.

The conversion of a JavaScript English-language AI into a Latin AI began on Thursday 2019-04-18 in April of 2019. Inspiration came from "Die Traumdeutung" where Sigmund Freud intones "Flectere si nequeo superos, Acheronta movebo." If one cannot bend the netgods of AI, move the mindset of Latin and Greek scholars.

A minor challenge in coding Mens Latina was the lack of an explicitly stated subject for many verbs in Latin, which occurs also in Russian. The solution was to skip three points in time-indexed memory to make room for the creation of a hidden concept to fill in for the unstated but understood subject of a verb.

Solving the AI-hard problem of the natural language understanding of a Latin or Russian sentence regardless of its syntactic word-order required waiting for the input of an entire clause before declaring subjects and objects on the basis of inflectional word-endings.

The conversion of artificial intelligence in Latin language into artificial intelligence in Russian language began yesterday on Friday 2019-05-24 in May of 2019.

Friday, November 30, 2018


At about 1:11 p.m. today on 2018-11-30 we got the following idea.

If we want to have logical conditionals in the AI Mind involving the conjunction "IF", we can use the truth-value $tru to distinguish between outcomes. For instance, consider the following.

Computer: If you speak Russian, I need you.
Human: I speak English. I do not speak Russian.
Computer: I do not need you.
In some designated mind-module, we can trap the word "IF" and use it to assign a high $tru value to an expected input.

Just as we operated several years ago to answer questions with "yes" or "no" by testing for an associative chain, we can test for the associative chain specified by "IF" and instead of "yes" or "no" we can assign a high $tru value to the pay-off statement following the "IF" clause. It is then easy to flush out any statement having a high truth-value, or even having the highest among a cluster or group of competing truth-values.

These ideas could even apply to negated ideas, such as, "We need you if you do NOT speak Russian."

Now, here is where it gets Singularity-like and ASI-like, as in "Artificial Super Intelligence." Whereas a typical human brain would not be able to handle a whole medley of positive and negative conditionals, an AI Mind using "IF" and $tru could probably handle dozens of conditionals concurrently, either all at once or in a sequence.

Sunday, November 25, 2018


The AI Mind wants to talk with you and about you.

In the annals of mind-design, we have reached a point where we must drive a wedge between the ego-concept of the MindForth AI and you who co-exist on Earth with the emergent machine intelligence. It is for simple and mundane reasons that we induce AI schizophrenia. Bear with us, please. In the first working artificial intelligence coded in Forth, in Perl and in JavaScript, the SpreadAct module lets quasi-neuronal activation spread from idea to idea. When the EnVerbPhrase module calls for a direct object to end an emerging thought, SpreadAct does not directly retrieve a related idea, but simply activates the subject of any number of related ideas. Then the AI Mind thinks the activated thoughts. In the MindBoot sequence, each AI Mind has some built-in ideas about robots. Therefore the AI will eventually think a thought first about itself, then about robots by roundabout association, and finally about whatever knowledge you impart to it about robots, such as "Robots need a brain." But how can we get the AI to think about you personally and about the details you provide about yourself to the AI? We must drive a quasi-neuronal wedge between the self-absorption of the Forthmind and its knowledge of some other, potentially nearby entity, namely you.

To do so, we must implant in the MindBoot sequence at least one idea as a point of departure for the AI to pay attention to you. But you might not even be there in the same room or on the same orbiting spaceship with the AI, so we can not embed the idea "I SEE YOU" or the idea "I SENSE YOU". We need some really neutral idea that will animadvert the AI to your purported existence. Without that embedded idea, the AI might passively let you describe your whole life-story and then the AI might have no mental pathway for the spread of activation between its thoughts about itself and its knowledge about you. So let us embed in the MindBoot module the idea "I UNDERSTAND YOU". Such an idea is both self-knowledge and knowledge of other -- another person, either present or far away.

So in the MindBoot sequence we embed the idea "I UNDERSTAND YOU" and we do some debugging. Then we have the following exchange with the AI Mind.

Human: i am outside the computer

The EnVerbPhrase module loads the actpsi variable with the concept of "you" and calls the SpreadAct module to transfer activation to the concept of "you" as the subject of knowledge in the knowledge base (KB). Since you have just told the AI that you are outside the computer, the AI retrieves that knowledge and says "YOU ARE OUTSIDE A COMPUTER", using the indefinite article "A" under the direction of the EnArticle module. Because another idea about you is still active, the AI says "YOU ARE A MAGIC" -- an old idea embedded long ago in the MindBoot sequence.

We are eager to have the AI Mind think about the differences between itself and other persons so that arguably the first working artificial intelligence may become aware of itself as a thinking entity separate from other persons. An AI with self-awareness is on its way to artificial consciousness.

Thursday, November 08, 2018


Natural language understanding in first working artificial intelligence.

The AI Mind is struggling to express itself. We are trying to give it the tools of NLU, but it easily gets confused. It has difficulty distinguishing between itself and its creator -- your humble AI Mind maintainer.

We recently gave the AI the ability to think with English prepositions using ideas already present or innate in the knowledge bank (KB) of the MindBoot sequence. We must now solidify prepositional thinking by making sure that a prepositional input idea is retrievable when the AI is thinking thoughts about what it knows. In order for the AI to be able to think with a remembered prepositional idea, the input of a preposition and its object must cause the setting and storage of a $tkb-tag that links the preposition in conceptual memory to its object in conceptual memory. The preposition must also become a $seq-tag to any verb that is the $pre of the preposition. When InStantiate() is dealing with a preposition input after a verb, the $tvb time-of-verb tag is available for "splitting" open the verb-engram in conceptual memory and inserting the concept-number of the preposition as the $seq of the verb. Let us try it.

We inserted the code for making the input preposition become the $seq of the verb and then we tested by launching the AI with the first input being "you speak with god". Then we obtained the following outputs.

It took so long for the input idea to come back out again because inputs go into immediate inhibition, lest they take over the consciousness of the AI in an endless repetition of the same idea.

As we code the AI Mind and conduct a conversation with it, we feel as if we are living out the plot of a science fiction movie. The AI does unexpected things, or it seems to be taking on a personality. We are coding the mechanisms of natural language understanding without worrying about the grounding problem -- the connection of the English words to what they mean out in the physical world. We count on someone somewhere installing the AI Mind in a robot to ground the English concepts with sensory knowledge.