Joscha Bach Quotes

How does... representation by simulation work? ...If you are a brain and you want to understand sound, you have to model it. ...Neurons do not want to do 20 Khz. That's way too fast for them. They like something like 20 Hz. So... you need to make a [which] measures the amount of energy at different frequencies. ...This ...in our ears ...transforms energy of sound at different frequency intervals into energy measurements... This is something that the brain can model. ...[A] neurosimulator tries to recreate these patterns. If it can predict the next input from the cochlea, then it understands the sound.

[O]ur best bet is not just to have a single classification with filtering. ...[I]nstead... take the low level of input and get a whole universe of features that is interrelated. ...[W]e have different levels of determinations. At the lowest level we have percepts. At a slightly higher level we have simulations, and on an even higher level we have a concept landscape.

If you take the activation at different levels of these networks and you... enhance this activation a little... you get stuff that looks very psychadelic, which might be similar to what happens if you put certain illegal substances into people and enhance the activity on certain layers of their visual processing.

AI has recently made huge progress in encoding data at perceptual interfaces. is about using a stacked hierarchy of feature detectors. ...[W]e use pattern detectors and we build them into networks that are arranged in hundreds of layers and then we adjust the links between these layers, usually using some kind of . ...[Y]ou can use this to classify [e.g.,] images and parts of speech. ...[W]e get to features that are more and more complex. They start with these very... simple patterns, and then get more and more complex until we get to object categories. ...[N]ow the systems are able, in image recognition tasks, to approach performance that's very similar to human performance. ...[I]t seems to be somewhat similar to what the brain seems to be doing in visual processing.

[E]verything that we're going to do is some approximation of Solomonoff Induction. ...[O]ur concepts cannot really refer to facts in the world out there. We do not get the truth by referring to stuff out there in the world. We get meaning by suitably encoding the patterns in our systemic interface.

What's the best algorithm that you should be using to fix your world model? ...This question ...has been answered for the first time by in the 1960s. He discovered an algorithm that you can apply when you've discovered that you're a robot and all you've got is data. What is the world like? ...[H]is algorithm is... a combination of Bayesian Reasoning, Induction and Occam's Razor. ...[W]e can mathematically prove that we cannot do better than Solomonoff Induction. Unfortunately, Solomonoff Induction is not quite computable.

Just as the extensive theoretical bodies of physics, chemistry, [etc.]... unified theories of cognition are not isolated statements discarded when... predictions [are] refuted. Rather they are paradigms... that direct a research program...

Functionalist psychology is... compatible with... scientific positivism, because it makes emperically falsifiable predictions... The... model is capable of producing [or predicting] specific behavior [and] [t]he model is the sparsest, simplest one...

The goal of building cognitive architectures is to achieve an understanding of mental processes by constructing testable information processing models.

According to [the hypothesis]... an implemented , has the necessary and sufficient means for general intelligent action. ...[A]ny system that exhibits general intelligence will ...be a physical symbol system. ...[A]ny physical symbol system of sufficient size can be organized further to exhibit general intelligence."

[A] functionalist model of cognitive processes might be implemented as a computer program (computationalism)... hand in hand with... Artificial Intelligence.

To understand... mind, we have to ask how a system capable of constructing has to be built...

[T]he notions we process... are systematically structured information, making up a dynamic system. The description of such... is the domain of cybernetics or systems science... constructive methods that allow the representation of functionality.

What the universe makes visible... to any observer... is... functionality.

Everything we know about ourselves is... ordering... over features available at the interface; we know of mental phenomena only insofar as they are patterns or constructed over patterns.