[I] think of the concepts as the address space for our behavior programs. The behavior programs allow us to recognize objects [also mental objects] and react... [A] large part of that is the physical world that we interact with, which is this thing... basically the navigation of information in space... [I]t's similar to a ... a physics engine that you can use to describe/predict how things that look in a particular way, that feel... a particular way, enough , enough auditory perception... the geometry of all these things... [T]his is probably 80% of what our brain is doing... dealing with that... real time simulation... [I]t's not that hard to understand... [O]ur game engines are already approximating the fidelity of what we can perceive... in the same ball park... just a couple of orders of magnitude away from saturating our perception, from the complexity that [the brain] can produce. ...[T]he computer that you can buy... is able to give a perceptual reality that has the detail that is already in the same ball park as what your brain can process.
cognitive scientist
, 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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For all practical purposes, the universe is a pattern generator, and the mind "makes sense" of these patterns by encoding them according to the regularities it can find. Thus, the representation of a concept in an intelligent system is not a pointer to a "thing in reality", but a set of hierarchical constraints over (for instance perceptual) data.
We probably need to build dreaming systems... [P]art of the purpose of dreams is... similar to a... generative adversarial network. We learn certain constraints, and then it produces alternative perspectives on the same set of constraints, so you can recognize it under different circumstances. Maybe we have flying dreams as children because we recreate the objects that we know, the maps that we know, from different perspectives, which also means from the bird's-eye perspective.
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[T]he relationship between cognition and neurobiological processes might be similar to the one between a car engine and locomotion. ...[A] car's locomotion is facilitated mainly by its engine, but the understanding of the engine does not aid much in finding out where the car goes. ...[T]he integration of... parts, the intentions of the driver and even the terrain might be more crucial ...
In cognitive science, we currently have two major families of architectures... One, the classical school... characterized as Fodorian Architectures, as... the manipulation of a language of thought, usually expressed as a set of rules and capable of . ...The other family favors distributed approaches and constrains a dynamic system with potentially astronomically many until... behaviors [of] general intelligence are left. This may seem more "natural" and well-tuned... Yet many functional aspects of intelligence... as planning and language, are... much harder to depict using the dynamical systems approach.
AI’s gradual demotion from a science of the mind to the nerdy playpen of engineering was accompanied not by utterances of disappointment, but by a chorus of glee, uniting those wary of human technological hubris with the same factions of society that used to oppose evolutionary theory or materialistic monism...
The failure to deliver on some of the early, optimistic promises of machine intelligence, as well as cultural opposition, lead to cuts in funding for cognitive AI, and eventually the start of the new discipline of Cognitive Science. ...Cognitive Science did not develop a cohesive methodology and theoretical outlook, and became an umbrella term for neuroscience, AI, cognitive psychology, linguistics and philosophy of mind.
Unlike physics, where previously unknown entities and mechanisms... are routinely postulated... and... evidence is sought in favor or against these... psychology shuns [this methodology]... Thus... cognitive psychology shows reluctance... to building unified theories of mental processes. ...Piaget's work ...might be one of the notable exceptions ...
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...