The system architecture must support artificial intelligence.


"Scientists have collaborated to create the world’s first 3D-printed “brain phantom,” utilizing a special magnetic resonance imaging technique (dMRI) to model brain fibers. This advancement is aimed at improving research into neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and multiple sclerosis by enhancing the accuracy of dMRI analysis software through the use of these detailed brain models." (ScitechDaily, Scientists Develop World’s First 3D-Printed “Brain Phantom”)


Researchers can use this structure to model 3D-printed large-scale neural structures that can make artificial superintelligence true, sooner than we expected. 


The living neurons that communicate with quantum computers are the model of artificial superintelligence. 


The living neurons that communicate with quantum computers are tools we can call artificial superintelligence. The artificial superintelligence can be the 3D-printed living brain that communicates with the quantum computers using neuro-implanted microchips. 

That kind of system is similar to a mini-brain. That researchers use in medical tests. The 3D bioprinters can make large-sized brains that the life support systems feed. The system can communicate with quantum systems using neuro-implanted electrons. And those half-biological systems are more powerful than humans. 




Artificial intelligence is a language model that creates other models searching and connecting information from multiple sources. That kind of code is hard to drive. 

The system must have effective data search tools. Those tools are the modems and internet connections that can give systems effective ports to the net. 

The quantum- or biological-quantum computer-based systems are the most powerful computers. That people ever imagined. The living neurons that communicate with quantum computers are the thing. That we can call artificial superintelligence. 


Seven steps of AI


Stage 1 – Rule-Based Systems 


Stage 2 – Context Awareness and Retention 


Stage 3 – Domain-Specific Expertise 


Stage 4 – Reasoning Machines


Stage 5 – Self-Aware Systems / Artificial General Intelligence (AGI)


Stage 6 – Artificial SuperIntelligence (ASI) 


Stage 7 – Singularity and Transcendence


Source: (Technology magazine, The evolution of AI: Seven stages leading to a smarter world)


https://technologymagazine.com/ai-and-machine-learning/evolution-ai-seven-stages-leading-smarter-world

Quantum lanterns are shining. 



"Illustration showing light exciting electrons in two molecules of the organic semiconductor known as buckminsterfullerene. The newly formed exciton (shown by the bright dot) is first distributed over two molecules before it settles on one molecule (shown on the right in the picture). Credit: Andreas Windischbacher." (ScitechDaily, Quantum Leap: Pioneering Exciton Imaging Transforms Semiconductor Science)



"Researchers at HZDR managed to generate wave-like excitations in a magnetic disk – so-called magnons – to specifically manipulate atomic-sized qubits in silicon carbide. This could open new possibilities for the transduction of information within quantum networks. Credit: HZDR / Mauricio Bejarano" (ScitechDaily, Quantum Computing Unleashed: Magnons Redefine Computational Boundaries)

Could this be the model for the new quantum computers or quantum chips? The fullerene and excitons are trapped in the Qube, and the system controls their energy level very accurately. The superpositions and entanglement were pulled through a graphene nanotube. And that makes this system suitable for multi-state quantum processors. 

"Frenkel exciton, bound electron-hole pair where the hole is localized at a position in the crystal represented by black dots" (Wikipedia, Exciton)

The thing: that makes exciton perfect for qubits is that exciton can destroyed after the use. But the other thing is that exciton is a clean particle. That means Exiton has no "dirty" information. The exciton is always sterile, and the system makes superposition and entanglement between excitons using their outer edge magnetic, or quantum field. Those outside fields of superposition are easier to make than the use of atoms. But also hydrogen atoms can used in this thing. The laser beam or some other energy stress can position electrons in a certain position and then that electron can act as an antenna that aims information in a certain direction. 


Artificial general intelligence or AGI is a tool that can any lower-level AIs. That thing means. That reasoning machines domain-specific AI and lower-level AI can be the "sons of the AGI". In that model, the AGI is the central AI or language model. That thing can create Reasoning machines. 

Reasoning machines can form domain-specific AI. The domain-specific AI is the tool that can make Context Awareness and Retention AI, and then that system can interact with "iron" or physical tools like robots, etc. with rule-based systems. The rule-based system is the new model of the kernel. That simple algorithm communicates with physical systems and acts as an interface for the AI-based systems. 

So this thing means that when the AI explores the mission, it creates lower-level AI to focus on that problem or mission. When AGI sees that it must control things in the flat it creates the reasoning machine. The reasoning machine will create domains for all electric equipment that it must control. 

Then the domain-specific AI can create the context-awareness machine. That system observes and controls things like ovens and coffee makers. The other domain creates algorithms that control the thermostats and lights. The upper-level system closes the lower-level systems in it. And there are lots of domains that this thing makes special algorithms for each domain. 


The AI requires powerful physical computers. 


The brain-imaging neural network where the supercomputers are in the hybrid star-ring topologies is the tool that can make AI more effective. The central unit is the pineal gland which shares information into the two or three segments that are emulating the human brain. The two larger blocks or domains are like cerebrums. If those two segments get the same answer. The system will follow those things. And if those two main segments get different answers the third segment selects from those answers. 

The same topology can used in quantum systems. The new exciton-based systems that deliver information between two fullerene balls where there is exciton trapped inside can make it easier to transform binary data into the quantum mode. And those fullerene balls can be the key to new types of quantum computers. 

The quantum computer searches its form. And there are many ways to make and stabilize the quantum entanglement. An exciton is a so-called quasiparticle simple electron that orbits the hole. The system can control the exciton's energy level more easily than hydrogen and other particles. The problem has been how to create a stable hole and stable exciton. 


https://scitechdaily.com/quantum-computing-unleashed-magnons-redefine-computational-boundaries/


https://scitechdaily.com/quantum-leap-pioneering-exciton-imaging-transforms-semiconductor-science/


https://scitechdaily.com/scientists-develop-worlds-first-3d-printed-brain-phantom/


https://technologymagazine.com/ai-and-machine-learning/evolution-ai-seven-stages-leading-smarter-world


https://en.wikipedia.org/wiki/Brain_in_a_vat


https://en.wikipedia.org/wiki/Exciton

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