AGI methods

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toborman

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Re: AGI methods
« Reply #15 on: July 08, 2014, 04:19:38 am »
Reasoning methods include: Deduction, induction, and abduction. Other reasoning methods might include analogy, and case-based reasoning, although these may be considered special forms of the first three methods.

For additional info you may take a peek at http://thinker.iwarp.com which is part of http://mindmap.iwarp.com/.

good luck on your project.  :)
« Last Edit: July 11, 2014, 05:42:47 am by toborman »

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Freddy

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Re: AGI methods
« Reply #16 on: July 10, 2014, 02:18:05 pm »
Topic split to allow this thread to stay on topic.

Welcome Toborman

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ivan.moony

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Re: AGI methods
« Reply #17 on: July 25, 2014, 11:47:16 am »
I just re-thought of something after a long time :D

A site could be built on address www.synthetic-mind.com. The site would contain a knowledge base, like an encyclopedia, but in structured manner, subject-predicate-object and similar for texts or structured data for math, chemistry and others. Besides knowledge base navigator, it would provide deduction solver for math and other areas and inductive finder for finding new formulas in physics and generally new knowledge about world. The project would be crowdsourced like wikipedia, but it would start with existing data from public encyclopedias, giving a start data boost (http://dbpedia.org/About, http://babelnet.org/, http://www.freebase.com/, http://people.mpi-inf.mpg.de/~gdemelo/yagosumo/).

So, people would read data and solve math and other problems, but when their computers are idle, it could be used for some inductive gentic algorithm to find new rules in the Universe, while analyzing knowledge base. God knows what new rules would be found, maybe some that humans could never thought about. Users could also choose at which area they want to invest their processor time. To avoid false data, users that want to enter new data would have a ranking board where they would be publicly ranked or finally eliminated from knowledge base.

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Don Patrick

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Re: AGI methods
« Reply #18 on: July 25, 2014, 03:52:47 pm »
I know two similar projects. One is project Cyc, where a small group of scientists has been collecting structured common knowledge for the past 30 years and offer it as a database for AI projects, along with an inference engine. Unfortunatly, implementation of this knowledge database and its structure leaves something to be desired.
The other project is NELL, the Never Ending Language Learner, which extracts facts from texts and websites, and relies on the online crowd to affirm or correct what it learns.
« Last Edit: July 25, 2014, 05:44:40 pm by Don Patrick »
CO2 retains heat. More CO2 in the air = hotter climate.

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ivan.moony

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Re: AGI methods
« Reply #19 on: July 25, 2014, 05:58:36 pm »
Those both projects do not have online problem solver and without that it is hard to get publicity. With math, physics and chemistry solver based on deduction we could get hits from twitter's and facebook's school and university pages. And I have strong indicies that "www.synthetic-mind.com" could hold programs and web pages beside data, making it a base for web 3.0.

So at the end it would be:
  • crowdsourced encyclopedia
  • scientific problem solver
  • exotic programming language implemented in javascript that can emulate any other programming language through its implanted parser
  • cloud based operating system that can hold and search programs, data and hosted web pages

All of this reminds me heavily of web 3.0 buzzword and I think it is reachable through free advertisement on twitter and facebook for the start. Especially if we make synthetic mind opensource for installing on whatever server.

Yeah I know, now I fly so hi, maybe I'll fall so low  :P
« Last Edit: July 25, 2014, 07:34:30 pm by ivan.moony »

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Freddy

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Re: AGI methods
« Reply #20 on: July 25, 2014, 06:43:34 pm »
Crowd sourced Encyclopaedia - you're probably going to get a few people telling you to use the Wikipedia API...

Ambitious project, but cool nonetheless  :)

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Art

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Re: AGI methods
« Reply #21 on: July 26, 2014, 12:18:39 am »
Or perhaps you could find a way to link into the NSA. They have collected and compiled information on everything and everyone! O0
In the world of AI, it's the thought that counts!

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ivan.moony

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Re: AGI methods
« Reply #22 on: July 26, 2014, 12:40:26 am »
I don't need NSA when I can see you all through this hole in the screen: o
Hey, you! I saw that!
And you! Put that finger out of your nose!
And you girl! Wear something on, there are children over here!
 ;D

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ivan.moony

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Re: AGI methods
« Reply #23 on: November 27, 2014, 06:03:35 pm »
I just thought of some direction of using Synth that could inspire someone:

What if a site would be built that would allow learning small fragments of english texts on demand (less than 1000 lines - like Don Patric's solution)? people could load texts and then ask questions about the matter. Simple answers could be given right away, but complex answers with a lot of proofing consumption could be processed in a larger amount of given processor time. And if a lot of machines would be running on the main web page, idle processor times could be shared to get answers for some complex questions.

People could vote where do they want to invest the most of their processor time. And if some answers are not yet achievable because of lack of data, triggers could be set up that would pop up "question solved!" window when answers get available (when enough data is collected from other users).

I have a good feeling about this one. Intelligent crowdsourced machines might visit us in some near future (while we are still alive). "IQ" could be a good name for such artificial assistant.

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ivan.moony

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Re: AGI methods
« Reply #24 on: January 01, 2015, 07:29:09 pm »
The idea is to have a programming language which behaves naturally in terms of cognitive process. If we have such a language, it would be an easy process to convert real world data to in-memory representation. It means that IQ would map data first from textual input stream to grammar structure and then from grammar structure to intrenal world representation. I think it is all about grouping different object into higher order constructs: words to sentences, sentences to theories, theories to Universe representation. The same goes for vision: different shapes are grouped together forming cognitive representation of wholes. All of this should be easily represented by language constructs.

I further simplified Synth's grammar to accept only: variable types, variable values and value dynamics. Complex structures like inference should be easily defined with just these three constructs which can represent any closed system in the Universe, including inference mechanism.

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ivan.moony

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Re: AGI methods
« Reply #25 on: January 02, 2015, 06:57:52 pm »
there is some technology I have in mind for a long time now. It is about classification of things in memory.

this is the basic idea: presentation

i guess this could be a starting point for learning new facts about the Universe.

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8pla.net

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Re: AGI methods
« Reply #26 on: January 03, 2015, 12:25:19 am »
Is your new technology like database tables, or is it different?
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ivan.moony

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Re: AGI methods
« Reply #27 on: January 03, 2015, 12:56:46 am »
it can be used as classic relational database tables, like having all tables in one big table.

But I'm more interested in classification object aspect. A column is classification base, a row field value is specific class the row belongs to and when a row belongs to some class it can be expanded by another columns of that class.

I imagine having objects in the Universe classified this way all in one big table. I even imagine predicates from classic logic being fitted in this like table which would bring typed predicates whose types would be defined by table header.

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8pla.net

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Re: AGI methods
« Reply #28 on: January 03, 2015, 01:41:50 am »
For the sake of friendly discussion, isn't one table, non-relational?   How are empty columns, in one big table, handled?
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ivan.moony

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Re: AGI methods
« Reply #29 on: January 03, 2015, 01:57:10 am »
Well, you can define multiple tables in one big table. In noted example in presentation there can be derived three tables from one, namely: scape type->GroundScape, scape type->SeaScape and scape type->SkyScape. If you think further, another parallel extraction can be made - to tables: engine->Otto, engine->Electric and engine->Jet and if engine is having specific value, it can be further expanded by another columns specific to engine type. You can even nest these sub-classifications, thus forming a table tree. So, basically, sub-tables aren't nothing more than a subset of rows of big table and each sub-table have rows inherited from parent table and rows expanded specifically for sub-table.

Empty columns? I don't understand...

 


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