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[I]f you look at the progression of AI models, it... went the opposite direction. ...AI started with linguistic protocols, which were expressed in fo… - Joscha Bach
" "[I]f you look at the progression of AI models, it... went the opposite direction. ...AI started with linguistic protocols, which were expressed in formal grammars, and then it got to concept spaces, and now it's about to address percepts. ...At some point in the near future it's going to get better at mental simulations and at some point after that we'll get to attention directed and motivationally connected systems that make sense of the world, that are in some sense able to address meaning. This is the hardware that we have...
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About Joscha Bach
, also known as “the wizard of consciousness”(born 1973 in Weimar, Germany) is a cognitive scientist focusing on cognitive architectures, models of mental representation, emotion, motivation and sociality. Achievements include research in novel data compression algorithm using concurrent entropy models; development of microPsi cognitive architecture for modeling emotion, motivation, mental representation. In 2000, Bach graduated with a diploma in Computer Science from Berlin, followed by a Doctor of Philosophy at Osnabrück University, Germany, in 2006. Before joining , he worked as a visiting researcher at the and the Harvard Program for Evolutionary Dynamics. Fact finding reports by the and found that Bach’s research was supported with more than $150,000 by the Foundation.
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Additional quotes by Joscha Bach
Because there is no narrow, concise understanding of what constitutes mental activity and what is part of mental processes... cognition, the cognitive sciences and the related notions span a wide and convoluted terrain... most of [which] lies outside psychology... This methodological discrepancy can only be understood in the context of the recent .
All our access to mathematics... is because we do computation. We can understand mathematics because our brain can compute some part of mathematics, very very little of it and to a very constrained complexity, but enough so we can map some of the infinite complexity and noncomputability of mathematics into computational patterns which we can explore.
Early AI systems tended to constrain themselves to micro-domains that could be sufficiently described using simple ontologies and binary predicate logics, or restricted themselves to hand-coded ontologies altogether. ...AI systems will probably have to be perceptual symbol systems, as opposed to amodal symbol systems...
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