Wednesday, July 3, 2019

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Cognitive Science's Failure to Become an Interdisciplinary Field - the Multi-Interdisciplinary Blindness

Discussion of mine regarding the paper:

"Perspective | What happened to cognitive science?,  10 June 2019

Available on Github:

IMO a big share of the problem lays in the whole researchers's and overall intellectual direction in the academic circles (and power-and-profit driven societies, modern slavery). It is narrow knowledge and world view, specialization is promoted, ones who obey and execute instructions of their superiors grow the ladder and become leaders, doing the same. The creative, wide-minded and really original ones are not leaders of the research.*

That is related to multi-interdisciplinary blindness, related to insufficient working memory capacity and faculties for understanding and representing the inputs generally enough so that one can encompass the concepts from different domains and contexts and think of them together.

BK calls it too simply "depth of structure".

* In the past there were exceptions, such as Alan Kay
** That survey paper reminds me of my cycle "What's wrong with Natural Language Processing" some 10 years ago, because to me NLP/Computational Linguistics should have been a part of the AGI, not what they were.

** Sorry for the sick formatting, I had to write it in external editor etc., this one is annoying, but not now.

See elaborate related discussions:


Circa 2009-2010 - series of 3 "perspective" articles

What's wrong with NLP, part I:

Monday, March 23, 2009

Note: now in NLP there are impressive results in NLG (generation), BERT etc. with such "mindless" vector representations, using current methods of machine learning, convolutions, "transformers" etc. however  it probably more or less emulates virtual sensory-motor interactions - by traversing and comparing huge corpora and how different texts/segments (mappings of sensory records) map and relate to each other, what's reasonable in what context. It is more advanced than as it was in the earlier simple frequency-based representations and inverse-frequency - frequency/probability of a token in current document, compared to average in the other documents etc.

#2 Friday, January 1, 2010

I will Create a Thinking Machine that will Self-Improve 

An Interview with Todor, "Obekty" magazine, issue November-December 2009   

- Where does the researchers' efforts should be focused in order to achieve Artificial General Intelligence (AGI)?

First of all, research should be lead by interdisciplinary scientists, who are seeing the big picture. You need to have a grasp of Cognitive Science, Neuroscience, Mathematics, Computer Science, Philosophy etc. Also, creation of an AGI is not just a scientific task, this is an enormous engineering enterprise – from the beginning you should think of the global architecture and for universal methods at low-level which would lead to accumulation of intelligence during the operation of the system. Neuroscience gives us some clues, neocortex is “the star” in this field. For example, it's known that the neurons are arranged in sort of unified modules – cortical columns. They are built by 6 layers of neurons, different layers have some specific types of neurons. All the neurons in one column are tightly connected vertically, between layers, and are processing a piece of sensory information together, as a whole. All types of sensory information – visual, auditory, touch etc. is processed by the interaction between unified modules, which are often called “the building blocks of intelligence”.

- If you believe that it is possible for us to build an AGI [Since you do believe], why we didn't manage to do it yet? What are the obstacles?

I believe that the biggest obstacle today is time. There are different forecasts, 10-20-50 years to enhance and specify current theoretical models before they actually run, or before computers get fast and powerful enough. I am an optimist that we can go there in less than 10 years, at least to basic models, and I'm sure that once we understand how to make it, the available computing power would be enough. One of the big obstacles in the past maybe was the research direction – top-down instead of bottom-up, but this was inevitable due to the limited computing


Tuesday, August 27, 2013

Issues on the AGIRI AGI email list and the AGI community in general - an Analysis
"- Multi-intra-inter-domain blindness/insufficiency [see other posts from Todor on the list] - people claim they are working on understanding "general" intelligence, but they clearly do not display traits of general/multi-inter-disciplinary interests and skills.

[ Note: Cognitive science, psychology, AI, NLP/Computational Linguistics, Mathematics, Robotics … – sorry, that's not general! General is being adept, fluent and talented in music, dance, visual arts (all), acting, story-telling, and all kinds of arts; in sociology, philosophy; sports … (…) ... + all of the typical ones + as many as possible other hard sciences and soft sciences and languages, and that is supposed to come from fluency in learning and mastering anything. That's something typical researchers definitely lack, which impedes their thinking about general intelligence. ](...) "


Tuesday, August 5, 2014


The Super Science of Philosophy and Some Confusions About it - continuation of the discussion on the "Strong Artificial Intelligence" thread at G+

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