Related to: [Name of Request for Research]
Please Do Not Just Take These Ideas and Run With Them Without Me!
I am attempting to increase my own involvement in Artificial Intelligence research and quantum computation. Please feel free to contact me at firstname.lastname@example.org. I would be more than willing to assist in the development or writing of a thesis or experiment (or at least get my name on there!)
I have worked extensively with tesla coils and I came to an epiphany a few weeks ago for the assembly of a practical quantum computer, but could not come to the appropriate materials required to build such a device. I came to a video of a demonstration of teslaphoresis at Rice University, and I think that the way it has been presented, teslaphoresis would be of great benefit on this frontier. I have had a discussion with Dr. David Redish (Neuroscience Prof) at the University of Minnesota and Dr. Babak Ayazifar at the University of California Berkeley (Electronics Prof) as well as discourses with a friend of mine that works at the Google facility in Mountainview, California.
There is a lot going on with regards to quantum computer / machine learning research, and my discourses are many pages long, so it might be difficult for me to condense the information effectively, but it all started when this Google colleague of mine commented on the difference between the arcs produced by vacuum tube tesla coils, which produce straight spearlike arcs, and the arcs produced by tesla coils with more modern switching components (IGBTs and MOSFETs) which seem to produce more jagged and diffuse arcs.
From my own understanding and what I’ve gathered, the human brain relies on quantum computing - specifically it allows all neurons to simultaneously “vote” to come up with a cohesive bound experience under a collective field potential that collapses in the form of impulses (the wavefunction collapse). Neurons are simply tiny RLC circuits and condense or coalesce under the form of an electromagnetic field, much like you have seen in your experiments. This forms receptor densities in the brain. Receptor types are very much similar to different kinds of switching components, and they produce different wavepackets - tonic/phasic signaling types known in neuroscience.
Dopamine receptors are like the vacuum tubes, they produce straight paths without much side branching - they reinforce connections - in the arcs - the dendrites.
I will attach a few photographs and documents and maybe you will be able to put the dots together. Quantum computers are vital because they allow the traversal of large amounts of data in tractable amounts of time and also break most modern cryptography, so there is a race for the production of the world’s first practical quantum computer that does not require kilowatts of power and subzero kelvin temperatures to operate. I believe that I have solved a great deal of the puzzle.
Backpropagation under this model is instantaneous and thus with such a computer, the fast fourier transform could be done, making it a practical quantum computer.
When I was working with my tesla coils I started to notice a strange phenomenon associated with designs employing vacuum tubes as their switching element. If you are unfamiliar with Nikola Tesla’s work, in his original designs there was a mechanical “switching element” - a spark gap, that would dump potential stored in a primary tank capacitor. With modern technology, we can digitally switch the coil - there is no need for such crudity in design. Modern switching elements are MOSFETs and IGBTs, and the plasma filaments look like a typical “lightning bolt” plasma discharge - jagged - diffuse.
you can see the fractal geometry of the arcs as they “branch out.” There is a certain degree of randomness associated with these arcs because of variations in resistance in the air in the room, the distortion of the ionization paths due to entropy (the heat causes them to rise and mutate and diffuse). What is interesting is that quantum fluctuations are actually amplified and manifest in the geometry of these arcs - of these plasma filaments. Now here is the mysterious part - in a tesla coil with a vacuum tube switching element, the arcs look much different - they look like little spears (or maybe lightsabers):
This is a profound difference, and my friend asked me about this. Several hours of discussion ensued. The reason for this is essentially just the difference in wave packets that the switching element produces. There is a direct relationship to this and the way that dopaminergic networks in the brain reinforce behavior.
Neurons are RLC circuits - they are like little tesla coils, and they have a resonance. They have different “switching elements” too - different receptors with varying densities across the brain’s 3 dimensional topology, and the circuits have varying degrees of resistance in a 3 dimensional topological gradient that are dependent upon neural connections. In AI research, these connections and their resistance are described as weights in the “connectivity” between neural nodes:
So what does this have to do with dopamine and tesla coils? The answer is tonic and phasic wavepackets. Dopaminergic receptors are more like “vacuum tubes,” and produce straight reinforced paths and prune out side connections. This was a fascinating realization because it also ties into a theory of cognition that I believe explains how the brain, as compact as it is, is able to come to decisions so quickly that are complex, and there are direct ramifications for the development of real-world practical quantum computers that do not require subzero kelvin temperatures or kilowatts of power to operate.
Parkinson’s disease is the disease of the paralysis of the will, and this model also explains parkinson’s symptomology
The brain is unable to cohere possibilities in a tractable amount of time into an impulse which is required for movement, in a similar way that a quantum computer can traverse a database in O(nlogn) time. There is a paralysis of will because the brain cannot effectively iterate through all of the branches effectively without the right switching type (dopamine receptors)
The arcs produced by the coils amplify quantum fluctuations, there is a degree of “randomness” associated with them, but it is like the Pope said, the universe was not made out of a principle of chaos - this chaos is fundamental to intelligence itself.
Classical models cannot explain this, the intelligence must come from a higher dimensional space - without a true “random number generator” the branches would not be able to effectively explore the possibilities necessary for intelligence in the human mind:
This also explains things like why there seems to be a fundamental randomness to the universe. Einstein said that “God does not play dice with the universe,” however, the universe appears to be random and run by probabilities. That is because the electromagnetic force is a smaller fractal representation of the gravitational force which permeates all 11 dimensions, and so it only approximates
I have been discussing this issue of chaos with one of my friends who is studying physics at the University of Texas at Austin. Chaos is a physics phenomenon that is not well understood, in the fields of science there are many principles that are not really well understood. The principle of turbulence, for example:
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How can something so orderly, like this smoke rising from a candle, become so decoherent and chaotic? What explains it? and how can you make sense of it, what theory brings it all together? The candle smoke falls apart into a mess. Somehow, gravity brings everything back together - gravity operates through 11 dimensional spacetime. Everything will come together, just not in a way that people can understand, like in this example, there is no equation or set of equations that can model turbulence, but I believe in Spinoza’s interpretation of God - a God of order and structure - there is a “plan” that brings everything back together. Our limitations in our own ability for inspection limits us to interpret the world fully. The mind works through electromagnetic fields, which are smaller fractal representations of the gravitational field, and so our ability to understand is fundamentally limited in this way, but if we work together we can approximate an understanding of the bigger picture, and that is why attempts to explain turbulence are only approximations.
Back in the early days of computing, there was the idea of “functional programming.” This approach quickly became inefficient and messy, and programmers became paralyzed by the number of pointers and underlying data, such that a bigger different approach was necessary. This approach became known as “object oriented programming,” and so these “objects” could have global effects across different pieces of code, and their influence could extend beyond their local block. In quantum computers, every idea is a field in the same way that in OOP, every idea is an object - except the difference is that a field has values at every location in spacetime, whereas objects are fundamentally limited in scope by the way silicon computers are produced
Turbulence is also an unsolved physics mystery - I have attached a discourse below discussing this in relation to the bitcoin graph
Turbulence is seen in all sorts of different domains - even religion - because every idea is a field with fractal ramifications, not a discrete data type or even “object.” Object oriented programming attempts to utilize the human brain’s “second memory system” as described by Dr. David Redish more effectively through the principles of inheritance, polymorphism, and scope. Information in this system is stored continuously, not in discrete space limited by the planck length.
There is even a simple mathematical proof that shows that a classical computational network would be fundamentally unable to devise of a quantum mechanical computational machine
Neurons are most certainly RLC circuits, like tesla coils