Bravo. You make a fine word salad. On Sun, Feb 17, 2019 at 9:48 AM A.T. Murray <mentific...@gmail.com> wrote:
> Steve Richfield asks: > > > 1. THEORY: In broad computer science terms, how does your system work? > > From what I can tell, it is an ad hoc text manipulation program capable > > of gathering information and answering simple questions within the > limited > > subject domains that have been programmed. Right? > > Aside: "ad hoc" (Latin "for this") means "special purpose" or > "non-general". No, Steve, my AI system is a very general emulation of the > human brain -- which I spent the first thirteen years (from Anno Ben > Goertzel 0-13) of my efforts deciphering into a > http://mind.sourceforge.net/theory5.html Theory of Mind. So it is not > simply a "text manipulation program" but rather a "concept manipulation > program." As such -- dealing with concepts -- it is not restricted to > "limited subject domains" but rather it may deal with any subject > imaginable. It does not deal with "domains that have been programmed" but > rather with "structures of thought that have been programmed", such as > Subject-Verb-Object (SVO) and query-formats such as "WHAT DO [subject]s > DO?" and "WHO [verb]s [object]?" > > Steve Richfield asks: > 2. APPLICATION: What will your approach be able to do that the machine > learning approaches discussed here can never ever be extended to do, and > why? > > As I understand ML, machine learning massages enormous data-sets to > discover patterns and to make predictions (such as Matt Mahoney et al. talk > about). My three AI Minds -- all basically the same program in Perl, > JavaScript and Forth -- deal with brief (small) inputs and not with the > statistics of large data-sets. The most significant achievement of each AI > Mind is Natural Language Understanding (NLU) as posed as an AI-hard problem > at the http://en.wikipedia.org/wiki/Natural-language_understanding > webpage. That is, my AI Minds understand natural language inputs insofar as > the minds assign the correct associative tags among the concepts mentioned > in each input. At first each AI could only understand single-sentence > inputs in the Subject-Verb-Object format. Then in 2016 the ghost.pl AI > became able to understand the input of indirect objects ("John gives the > BOY a book") and prepositional phrases ("John works IN the school"). Now in > 2019 the AI Minds are beginning to understand the extremely complex use of > conjunctions. Please see http://ai.neocities.org/EnVerbPhrase.html for > how the AI Mind can shorten multiple ideas AND-ed together into a run-on > sentence. > > MP says: > > in one of his "earlier" journels, he references a "boulematic > accumulator" - > > in normal lingo, it means neuron, like a neural network neuron. > > That document was my private journal of AI theorizing. "Bouleuma" is the > Greek word for "will" or "volition". I could have written "volitional > accumulator". In the http://ai.neocities.org/Volition.html webpage on > 2019-02-08 I wrote: > > "3.B. A chief characteristic of AI volition is the integrative nature of > the will as it contemplates a candidate for action. Feelings or ideas in > favor of a proposed initiative gradually move the Volition module towards > the threshold of launching the motor execution of the proposed behavior, > while contrary feelings and countervailing ideas delay or even prevent the > launching of the motor initiative." > > Joshua Maurice wrote: > > Probably most people here haven't had time to look at 15k lines > > of code and form an evaluation of it. > > As I gradually do more and more debugging of each AI Mind, people will not > need to inspect the code so much as simply to interact with the AI. > > Cheers, > > Arthur > > > > On Sat, Feb 16, 2019 at 10:50 AM Steve Richfield < > steve.richfi...@gmail.com> wrote: > >> Arthur, >> >> I have been one of your few supporters, but if you are going to usefully >> engage with the present audience, you REALLY need to answer two questions, >> that if done well will lead to other questions, that will lead to a useful >> conversation... >> >> 1. THEORY: In broad computer science terms, how does your system work? >> From what I can tell, it is an ad hoc text manipulation program capable of >> gathering information and answering simple questions within the limited >> subject domains that have been programmed. Right? >> >> 2. APPLICATION: What will your approach be able to do that the machine >> learning approaches discussed here can never ever be extended to do, and >> why? For example, my system works to diagnose chronic illnesses in a way >> that can NEVER EVER be equalled with ML approaches. From what I can tell, >> your system might be extended to make a really good military inventory >> program. >> >> As with all AI programs, their authors have dreams for them that exceed >> everyone else's expectations, and you and I are no exceptions. I understand >> that ONLY ad hoc logic will EVER be capable of incorporating human >> understanding of our world into a computer, a simple fact that is >> universally rejected by others on this forum for NO good non-religious >> reason. So, until others here wake up, at minimum, I should be able to >> relate to your postings. If you can't carry me along, then you truly are >> COMPLETELY wasting your time and your life by continuing to post. >> >> Steve Richfield >> >> >> *Artificial General Intelligence List <https://agi.topicbox.com/latest>* > / AGI / see discussions <https://agi.topicbox.com/groups/agi> + > participants <https://agi.topicbox.com/groups/agi/members> + delivery > options <https://agi.topicbox.com/groups/agi/subscription> Permalink > <https://agi.topicbox.com/groups/agi/Tc360a468d4050822-Mb0b69c64698c1ee9a2a63d37> > ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Tc360a468d4050822-M325d2bf6b28b8dd4f6d95642 Delivery options: https://agi.topicbox.com/groups/agi/subscription
