A brain-like implementation of a Turing machine

In summary: However, they’re not perfect. They don’t account for noise and they don’t generalize well. They also don’t learn from experience."Neural nets are quite common in AI. We even use evolution algorithms to hone them. However, they’re not perfect. They don’t account for noise and they don’t generalize well. They also don’t learn from experience."
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At first I should say that this thread involves many scientific fields and I don't think there is any correct section of PF to put it under so I just went with the engineering.
One of the greatest mysteries(maybe the greatest) that science is trying to solve today, is the emergence of consciousness from the chemical and electrical processes of the human body, specifically the brain.
Its really amazing that there is this system made out of all this material ingredients and operating under all this physical laws, that accommodates something as seemingly immaterial as our consciousness. But if you think about it, you'll see that there is a similar thing going on with computers. There is all this hardware that ultimately does everything and some form of output that gives us the result, but still, when you write a function in C++, that function has no physical manifestation. The underlying hardware is just sending some electrical signals through logic gates, etc. If there is any kind of programming language that can be said to have a physical manifestation in the underlying hardware, is the assembly language. So in a way, there is actually some abstract thought going on in our computers and that is actually how we have managed to get so much work out of computers, by creating abstractions over abstractions and so on over them, so that we can communicate more and more complex ideas to them.
This makes me think that although computers have far less capabilities when it comes to consciousness, it doesn't mean that they can't be a starting point to the understanding of the human consciousness. But how can we use them in that way?
Well...Although when we think about the implementation of computers, the picture of a dozen electrical circuits comes to mind, these electrical circuits are only an implementation of an abstract idea called the Turing machine, a machine with a way of getting an input, running it through an algorithm and returning an output, and it should be able to handle any algorithm. So...maybe electrical circuits have a fundamental limitation in implementing such an idea. Maybe there is an implementation out there that gives this idea far more power than we observe with current computers. And when I look at the human brain, I think that maybe that implementation is actually a system involving a combination of electrical and chemical processes.
So I think there can be a new direction in researching consciousness and that is trying to find a brain-like implementation of a Turing machine.
Please feel free to share your thoughts or any relevant material.
 
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I think the issue is we know how computer electronics work at the operational level and we've built libraries of code to harness the power. We also know that the brain must be doing something similar but we can't yet find the CPU and the cache units as they seem to be interspersed within the brain as a whole.

In some ways consciousness is like an ocean wave. The wave is a result of the water molecules moving in a certain way. To us the wave moves forward toward the shore but to the water molecules they just move in a small circle.

https://ci.coastal.edu/~sgilman/770Oceansinmotion.htm
 
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You described a neural net and they’re quite common in AI. We even use evolution algorithms to hone them.
 
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1. What is a brain-like implementation of a Turing machine?

A brain-like implementation of a Turing machine refers to a computer system that is designed to mimic the structure and functioning of the human brain. This means that it is able to process information in a way that is similar to how the brain processes information, using neural networks and learning algorithms.

2. How does a brain-like implementation of a Turing machine work?

A brain-like implementation of a Turing machine works by using neural networks to process information. These networks are made up of interconnected nodes that perform calculations and transmit information to each other. The system also uses learning algorithms to adapt and improve its performance over time.

3. What are the potential applications of a brain-like implementation of a Turing machine?

There are many potential applications for a brain-like implementation of a Turing machine, including artificial intelligence, machine learning, and data analysis. It could also have uses in fields such as neuroscience and cognitive psychology, as it may help us better understand how the brain works.

4. How does a brain-like implementation of a Turing machine differ from a traditional computer?

A brain-like implementation of a Turing machine differs from a traditional computer in several ways. Firstly, it is designed to mimic the structure and functioning of the human brain, whereas traditional computers are based on the von Neumann architecture. Additionally, a brain-like implementation of a Turing machine uses neural networks and learning algorithms for processing information, whereas traditional computers use a central processing unit and algorithms.

5. What are the potential advantages of a brain-like implementation of a Turing machine?

One potential advantage of a brain-like implementation of a Turing machine is its ability to process and analyze complex and unstructured data. It may also be more energy-efficient and faster than traditional computers, as it can perform multiple tasks simultaneously and adapt its performance based on the data being processed. Additionally, it may have applications in artificial intelligence and machine learning, leading to advancements in these fields.

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