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A designed language is very precise so that thoughts formulated in it are universally understood – everyone will know exactly what you mean, with no place for misinterpretation. A disadvantage of this, I think, is limiting the ability to use metaphors, basically limiting human creativity – you end up with a clear language but one that lacks the “vibrancy” of a less clear language.
I would say in terms of complexity I will look for patterns and if I don’t find any obvious patterns (if it looks random) I would consider that as being a complex system, potentially irreducible.
Weather patterns, bubbles in boiling water, cream mixing with milk are examples that come to mind as potentially complex, computationally irreducible systems.
This is interesting, but I don’t understand one thing: how can we use a Rule 30 or Rule 110 Cellular Automaton if it’s computationally irreducible? How can we understand and program it to do whatever we need it to do if the only way to see what it does is to run every step of its computation? I see only computationally reducible automatons as useful tools to perform predictable computations, the kind of computations that we understand and can use. Where am I mistaking?
I think one way is to observe a particle in superposition – that’s going to be random by default. There’s even an app called “Universe Splitter” on iOS that allows you to perform a measurement on a particle in superposition and based on its outcome do a particular action which is guaranteed to be random.
I am not exactly sure how does the Rule 30 Cellular Automata is random – I mean, sure, the outcome looks random, but how do you choose a subset of that result set? Isn’t the decision of choosing going to be determined? Isn’t it the same as using a random number generator with a seed? Or is that actually the point, that’s what a random number generator uses under the hood?
I think all areas could benefit. Sight and hearing, besides movement, are my main targets for improving/re-establishing using BMIs. Another one that I’m personally curious about is creating new qualias, new emotions, but that requires us to do experiments on people (to have them report back what they feel) which has ethical implications thus it’s difficult to do.
Really fascinating examples. Although I will stay focused on my personal goal of understanding how qualia arises from brain activity. The motor part of the world can be explained in a physical way (electrical activity in the brain that causes a particular muscle to fire, which is completely causal and physical), but my question is if there’s any way to use a similar take on how qualia arises?
I think first off I would try to find a less invasive way to gather the brain data. Then I would try to create a new, never before seen qualia – something that feels different than our regular senses. Of course, this would take a lot of work in order to determine what generates qualia in the first place, but if successful it would be one of the greatest discoveries of all time, in my opinion, if not THE greatest discovery – we would understand how the brain creates qualia and what’s so special about a particular type of neuron and its receptors – why do dopaminergic neurons create a different sensation from serotonergic ones, for example? Is it the location in the brain? Their molecular structure? The way they encode the information? The way they alter the brain waves? So many questions to ask.
I think it was an interesting course, it was fun to learn about the power rules of scaling and about the energy limitations in folding the brain. I am still interested in understanding conciousness and what’s so special about the cortical neurons that isn’t special about the other neurons in giving rise to consciousness and the hard problem of consciousness, namely how come some material like brain tissue gives rise to a subjective internal world or qualia? That’s really the big mystery that I’m interested in.