In Ben Goertzel's Wiki
"Knowledge is represented in a network whose nodes and links carry probabilistic truth values as well as "attention values", with the attention values resembling the weights in a neural network."
attention values resembling the weights .. in a neural network .. attributed to the attention cognitive part of processing the knowledge body .. upon which its strength and efficiency is assessed by ..
weights ..largely based on ..fatigue .. engaged neurons arriving to their threshold limits .. therefore controlling human cognitive functions .. attenuating the effect .. even the validity of the outcomes achieved .. by its application ..
a corresponding factor that .. an artificial AGI based cognition model ..the deployment of its cognitive functions ..does not take on board .. does without it .. human cognition ..and AGI cognition ..compared like-for-like .. presents .. sort-of unfair advantages .. for AGI-based cognition ..
knowledge is represented in a network whose nodes and links carry probabilistic truth values .. knowledge ..as network ..of nodes and links .. being based upon ..
probabilistic truth values .. quantum mechanics at bay .. superposition of states and the like .. the mechanics required .. their physical presence necessary (but not sufficient(?)).. brought into existence .. once by .. nature's evolutionary machinery .. the ..wetware .. in the brains of human individuals .. and now [human cognition]-manufactured enabled .. software induced .. foreseen AGI .. software-based hardware .. soft-hardware ..
AGI cognition .. certainly ..once it is presented .. has, what is required .. will be populated ..with an array of cognitive functions necessary .. spurting out intelligence ..
being presented as .. an interface .. a conduit .. even as a ..gateway ..
probabilistic truth values .. the mechanism .. its intuitive appeal holds true .. for both .. human cognition ..and ..AGI cognition .. human cognition ..though, disadvantaged ..on the attention field ..fatigue-based weights .. this presumed disadvantage .. explain ...
Why is AGI research so unpopular??
human cognition .. resists ..its dethronement from the pedestal has put itself in .. resists vehemently .. and to my opinion foolishly .. as not enough self-knowledge has accumulated .. acknowledged, heeded and abided by .. as a result .. the terminator-scenarios, the AI robots all the popular folklore .. out of sci-fi and film industry .. the myths created and propagated .. of future evolution of societies .. always admonishing for the plight of humanity
intrinsic inherent conditions .. the reflexes built over millennia of human development ..
human frailties .. out of the state of development .. under the prerogatives human societies were nurtured in .. the prerogative of power .. dressed up with .. scared to the bone .. that any development of artificial cognition .. will automatically acquire all the human cognition .. attributed nasties .. the baggage that necessarily ..any kind of cognition ..carries
as cognition is taken ..is used for .. the subjugation to the will ..of the stronger
the submission ..of individuals attributed with weaker cognitive powers .. to the will of individuals attributed with stronger cognitive powers ..
the reference to strong AI .. bring forth extensions .. out of mangled-up concepts adhered by societies .. attributed to strength .. as what is connected with .. for individuals to do their bidding .. and not .. out of the concept derived .. out of strong nuclear forces conceptualisation ..
In "Patterns, Hypergraphs and Embodied General Intelligence" by Ben Goertzel
"The most articulate argument so far created in favor of the in-principle possibility of AGI is Marcus Hutter’s  theoretical work on algorithmic information theory and decision theory, which involves positing a very general mathematical definition of intelligence and then proving rigorously that arbitrarily high degrees of intelligence are possible given arbitrarily large amounts of computational power. If Hutter’s definition of intelligence is accepted, then his theorems show that with enough computing power, making AGI is trivial and can be done in a few dozen lines of easily-formulated LISP code. But this insight doesn’t help much in creating practical AGI systems using tractable amounts of computational power – probably because, as per , the human brain consists of a collection of more or less clever tricks for achieving more or less general intelligence within strict computation-power constraints."
tractable .. amounts of computational power .. human cognition evolved .. having to solve ..intractable problems .. and the computational power behind it .. what manage(-s or/and -d) .. to provide solutions to such intractable problems ..witnessed by humanity's survival and current growth .. out of .. the sentence .. 'human brain consists of a collection of more or less clever tricks' .. what are these tricks? .. still elusive? ..
Ben Goertzel's embarked project to bestow upon us AGI intelligence and the human brain collection of more or less clever tricks, still elusive