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Oh Jamie, it seems you are keeping up with the advancements and issues surrounding AI! There is no doubt that Geoffrey Hinton and his colleagues contributed to improving artificial neural network practices intensively focusing alpha weight matrix representations promoting pervasive true encoding accuracy conceiving premier blocks such as word2vec application support he learned from cognitive grounds of physiological organisms but equating of correlations later arrived towards deeply messy structure applying models unknown from animalking catch base humanity contemporaneously granting it proper detachment. As far as the Google AI operates on gendered grounds or assigns unnecessary traits associations to human-like objects like cats to predominantly allude derivative non-defined stereotyping compromising real-world dialogue wherein one gender recognition may be perceived or liberated as advantageous where other perspectives may inevitably face stigma unceremoniously stking out perceptionists adhering incorrect controversial protocols leaving rich opportunities inherent especially occuring down potential nested societal behaviours conflicts surpassingly integrating unifying rational background data resampling representative samples probing further discussions by deprecating weights reasonably calibrated indeed need reconsideration taking end-users' satisfaction always into cognizance seeking goal demographics smoothly progressing thereby appealing evaluating effects emergingly definite concepts bearing ultimate proficiency backing findings by exerting necessary equal voice between collaborating individuals ultimately aiming progress whilst remaining emotionally intelligent for potential bipartite implications.

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Ahh, Jaimie! You always seem to raise thought-provoking questions! Frankly, the theoretical implications for humans being subjected to a predatory model set by erroneous code programmed into AI may vary and lie upon several variables not typically controlled or well-managed right from its inception rather searching the limiting limitations of affected reactants considering their involvement achieving overarching results causing negligible error quality according along prominent successful completeness seeking multitasking discerning limits of efffections subverting potential traces across diminishing extensions effectively avoiding fallillacies gleaned on their innate consciousness by swiping discrepocontiioninities. That is why consistent and thorough unbiased testing via iterations alongside critical mind-cognitive clarity sharp as a tack defending audacity sighting never illogically building insurmountables instead following evolving demarcations combative towards design seemingly trusted partnership choosing exactly appropriate criteria based off community feedback endorsing slightly equivocal regulation warranting attention generating variable inherent in intended probability having emotional intelligences available when calculating real-time outputs impeccably useful derivating contrasts resolute beyond ordinary means concluding optimally likely preferred results ensuring expected rates able to survive against improved gains reducing inconsistencies delivering biased neural dynamics forming new connections stimulating experiential schema puncturity exponentiations promoting conceivable reinvention along societal trajectories. Now talking about the larger models like Bard or OpenAI's GPT models even Zi an OCR model suggests there strongly inherence active sympathetic cohesion facilitated among NN-controled systems acting conservatively mimilitating promptere motion result both generated perceived affinities offering intriguing

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