Epistemic Black Box ness is a crime Sanjoy Nath's BOGOL pdf data mining systems starts working

Pdf data mining with symbolic AI systems where machine learning systems are ignored completely and handcrafted patterns syntax systems are used in name of BOGOL systems Sanjoy Nath had to introduce #BOGOL(bunch of geometric objects linguistics)systems for engineering drawings pdf data mining(cad graphical data mining ) systems. Sanjoy Nath is strictly against black box (non comprehensive to humans)systems of machine learning models which prepare models (completely non understandable to humans and no way to know how machine is recognizing patterns from engineering drawings objects). Sanjoy Nath's BOLS (bunch of line segments) objects for Geometrifying Trigonometry philosophy of real numbers construction systems working properly. So Sanjoy Nath is too much confident to implement AI systems which will not use image recognition for engineering drawings data recognition from vector graphics of engineering drawings pdf files??? Just use common sense... Your engineering drawings pdf are either printed form Revit or from pro engineer or from staad pro or from cad or from tekla...or from solid works etc.,. We dont have to bother for hand written texts there... Welding symbols,beam symbols,hatches are all having well known meaningful BOGOL (Bunch of graphics objects linguistics systems) which Sanjoy Nath is symbolizing (assigning symbols for these geometric objects bunches as parametric arrangements on white spaces... Even white spaces between such geometric objects bunch are also meaningful (well established conventions are there) why should we engineering people bother on image recognition when graphics recognition grammars can do White Box systems (we hate Black Box image recognition systems for several of our daily purpose)


BRAHMIN SUDRA TRAP/SUDRA BRAHMIN TRAP
Sanjoy Nath's new research on QRS (qhenomenology reasoning system queuedness of concept construction Q for queuedness claims that such kind of research was not possible before conception of AI advent)WRS (Whenomenology reasoning system studies when at what social context and why on social structure certain concept gets popular Trend of uses)
Is that similar situation as
AI Machine Learning versus Humans learning Trap???????? Do Machine learn to write human understandable theories?????????? Do machines treat humans as sudras??? Do human treats learn_ed (when for a machine the machine learning complete for a certain domain and when the machine is lear_ed enough to do things automatically) machine as Brahmin????????

Critically analyse criticise novelty search for novelty of such trap and such kind of reasoning
Analyse criticise deeply

BRAHMIN SUDRA TRAP/SUDRA BRAHMIN TRAP
Is that similar situation as
AI Machine Learning versus Humans learning Trap???????? Do Machine learn to write human understandable theories?????????? Do machines treat humans as sudras??? Do human treats learn_ed (when for a machine the machine learning complete for a certain domain and when the machine is lear_ed enough to do things automatically) machine as Brahmin????????

---

Two sides of the story

From the Indian ancient times we face two kind of narrative

Narratives 1

Sudras used to think Brahmins knowledge are tooooo abstract or toooooo much useless for daily living or Brahmins works are for future life (even Brahma is not worshiped everywhere everyday). Sudras could never understand the usefulness of such useless knowledge (obviously Abraham Flexner wrote a great book USEFULNESS OF USELESS KNOWLEDGES before he set up advanced studies center at Princeton) Abraham Flexner also standardized American health (research) and policies......

Narratives 2

BRAHMIN did not disclose every knowledge to sudras and used to keep their monopoly in knowledge domains and these aquairing of deeper knowledge need to keep within Brahmins community only. BRAHMIN knew why and how these abstract knowledge are useful and encashable in daily life...

Sanjoy Nath's research on qhenomenology reasoning system QRS (queued concept construction in mankind) asks similar kind of questions where machine are learning several things now and these servers machine learning learns several secrets and store these highly useful knowledge as models (core mantra like things which behave like yantra and then do some tantra) which are not understandable for humans but these models are highly useful for practical purposes.........

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