reply to post by teyateya
Hmmm, this keeps popping up, people dismiss me, asking why I'm here at ATS as if I had better things to do. Well it has to start somewhere. ATS got
me my first 500 views of my video on the YT. First I have to go viral, then I have to sell books, then once I have $ I can actually prototype my
inventions, but here is the gist of the NHP:
NEUROMIMETIC HYBRID PROCESSOR WHITE PAPER
The NHP is a computing device born of the biomimicry methodology. Its purpose is to replace silicon which is nearing the end of its capacity. Compared
to the other silicon alternatives it stands out as having the only true neuromimetic architecture.
BIOMORPHED ELEMENTS
-neurons - polymer sheathed dendrimers (encapsulated electroactive objects)
-neural fluids - TCNQ/ polyelectrolyte saturated solution
-synapse - thermionic injection, FET induced arcing from source to drain, spontaneous clamping, floating deposition
-neural network - back propagation, feed forward, discrete time recurrent, continuous time recurrent
-determinism - transcopic electrochemical noise analysis, impedance spectroscopy, phase states vs. transition points
COMPONENTS and ARCHITECTURE
The NHP consists of 4 self metalizing polymer films and 2 semiconductive polymer TFT's arranged into a cube shape. Inside this cube is 5-10 cc's of
a TCNQ/poly-electrolyte/dendrimer suspension. On the outside of the cube is a scalar interferometer, it is a thermionic injector for the suspended
nucleation of the suspension required for certain neural networks – its scalar bottle is the “thalamus”. This mini-HAARP is coupled to another
which does a non-invasive BMI with any part of the nervous system.
Since the NHP is a hybrid computer, the digital TFT or analog suspension can act as the driver depending on the desired neural network. Unlike other
computers, the NHP derives its determinism transcopically. This means that it is a molecular-quantum computer. What this equates to is a binary system
with a fuzzy system enfolded within the fractional dimensions between 1 and 0.
The self-metalizing films are reference/auxilary electrodes injected with stochastic resonance, each opposing set has a different noise which creates
a co-chaotic medium out of the suspension, in effect keeping it metastable and homogenous. The TFT's are the working electrodes perpendicular to the
self-metalizing films. They are injected with a collapsing or periodic waveform signal. As the signal cascades through the phase states, it modulates
the stochastic resonance via sympathetic resonance, phase lock, handshake or beat. This is what clamps the suspension into a molecular wire and gives
a pathway weight. Once the pathway or filament is formed it will have non-volatile memory.
ADVANTAGES AND PROPERTIES
All the known advantages of a hybrid architecture are here. All the advantages of a fuzzy system are here. What is unique to the NHP is that it has
incredible parallel processing power due to the shear number of filaments. Mobility and storage density are roughly 10,000 fold greater than that of a
silicon chip.
The true innovation to computing is the potential for AI and the elimination of interface peripherals.
These processors, since they are neuromimetic, are ideal for biomimetic humanoid robots. Each neural network can subsumptively regulate a specific
organ/subsystem. Visual, haptic, audio, kinematic, biological, power, pneumatic and hydraulic systems can be matched to the ideal neural network.
Custom neural networks can be made by rearranging the components.
TRANSCOPIC DETERMINISM
In quantum computer theory it is believed we must create quantum error correction algorithms or filter the noise to get a dependable processor.
This is resistance to chaos. The quantum foam is literally the most chaotic phenomenon. To resist the quanta chaos is the most futile thing a
neuromimetic computer could do. We overlook the role stochastic noise plays in our own consciousness so we don't consider it when designing a
computer. We measure for the most part according to periodic or orderly methods. We also don't consider the underlying chaos in our macroscopic
patterns.
The processors I designed utilize two signals, stochastic and periodic. These represent the chaos of the foam and the periodic functions of the
macroscopic brain - alpha, beta, delta, Schumann resonance... Carrier and modulation functions are reversible depending on the desired neural network.
Sympathetic stochastic resonance is the key to designating weight to a given path. The resultant beat of these two signals meshing is what brings
order out of chaos. The more reinforced this analog memory becomes, the more weight it has and the more order it attains. But this type of order is
neither pure chaos nor pure order as are the noise and periodic signals. The periodic signal maintains what is modulated but the stochastic noise
signal is what makes it associative or holographic to the rest of the suspension.
The NHP doesn't have to "make an end run around the difficulties posed by the laws of nature" like the myriad of other Silicon Alternatives
striving to beat Moore’s Law. Molecular, Biological, and Quantum computing consortiums, many of which are sponsored by DARPA, may use biology
inspired algorithms but they ultimately fail to mimic biology. The potential seems to be greater than results and the Silicon Industry feels safe
because of this, but even the neural networks that run on silicon fail to mimic because, after all, they represent a 2D digital medium.
Biomimicry is a new science which treats nature as the standard for judging the "rightness" of our innovations. Nature is acknowledged to have
billions of years of R+D and inherent superiority. Many old sciences are coming around to this humility and reverence for what nature can do, and it
is most pronounced in the computing architecture fields. It is normal for humans to compare biology to the machine of the day - the brain is compared
to a computer often but never the other way around. A new model of the brain, biomimicry methodology, and the NHP which this model supports, may make
brain and computer truly synonymous.
I took a class at Cornell University - Systems on a Chip: Interdisciplinary Computer Engineering. I have witnessed first hand the schism between the
self-educated, and the formally educated, the wise intentions of interdisciplinary endeavors and how they fail. I saw how, despite the multiple
professors, all the students remained specialized. I was disappointed by the class because it didn't teach anything about how a team should work
together; none of the professors worked together, the individual subjects were never tied together. The grad student who organized the class and let
me sit in on it saw the NHP, thought it was "great," and said he'd try to get some professors to look at it. One said that that kind of technology
is "at least 20 years away." Another looked at it and said it was over his head. This discrepancy in attitude and knowledge is a big concern and
it's what gives me an advantage as an independent. I left the class because one day the class had to break up into groups. I couldn't be in a group.
The grad student, in an emphatic tone, told everyone that, "this is about quantifying. Do NOT use your imaginations!"
This statement is pure blasphemy to an inventor.
The NHP was conceived admittedly about 9 years ago in the "EUREKA" fashion with two words: "CRYSTAL BRAIN." It wasn't until about a year ago that
it all came together when I did some intensive studying online to find components. In that process I learned of all the other silicon alternatives and
saw how those efforts were not yielding very much. It was my intent to adhere to biomimicry methodology and the reason was simple: I should be able to
reverse engineer the very thing that allows me to - i.e., the brain. Whereas corporate and academic circles may frown upon my methods for doing this,
it nonetheless worked. Call it an unfair advantage but one brain is all that's needed to explain itself. Of course when studying and associating is
all that's demanded of you, being exceptionally productive is possible. I had no red tape to contend with, or people, or deadlines.
Basically, I feel that I would be an ideal interdisciplinary team leader for the NHP or any endeavor.
An interesting anecdote
At the same time I took my class at Cornell, a man named S. Rosen took it upon himself to be my business advisor. He arranged a conference call for me
with a consultant from Compaq to help determine the feasibility of the NHP. After a few minutes he told me that what I had was, "A bowl of goo" and
that I was, "just another kid trying to reinvent the wheel" and that the NHP was, "a solution looking for a problem."
I then realized that as a representative of the silicon industry he was either threatened or ignorant or both.
PROPRIETORY ISSUES
The only setback to building a proof-of-concept prototype, besides finding funding, facilities, and a proper team, is in acquiring the individual
components. Polymer thin film transistors are relatively rare. The manufacturer of the TFT that the NHP would use is Opticom. It would take an entity
like ______ to sway them into the use of their TFT. The self-metalizing polymer is available through NASA. The impedance spectroscopy software (the
NHP driver) is available through Gamry. The polyelectrolyte, TCNQ, and dendrimers should be available through various university sources.
The name escapes me and I’m away from the internet right now (February 2010) but in 2001 when I invented this I had not known of “In its Image”.
Google it with “Skynet”. This is the true driver of the NHP. When you dial in the proper ratio of fuzzy between 1 and 0 or of life and death you
get emergent novelty.
APPLICATIONS
Now obviously the first thing ______ is interested in is Encryption. The NHP could definitely handle that, but the it was designed to answer decades
of questions about AI, soulcatching, massive parallel processing, and even some paranormal questions (ex: in quantum theory we should be able to turn
on the NHP with direct thought).
The NHP can recreate any gate or neural network - it is universal in every sense.
The NHP is ideal for all robotics apps, all physics modeling, math.