"A new model developed by Flatiron Institute researchers proposes that biological neurons have more control over their surroundings than previously thought, something that could be replicated in the artificial neural networks used in machine learning." (ScitechDaily, Supercharging AI With New Computational Model of Real Neurons)
The virtual neuron is a group of databases that are linked together. The databases are connected like neurons in human brains. And the routers between those databases make them interact together like neurons.
Those routers and wires that play axons can be real or virtual systems. The physical system means that databases are in different hard disks, and the routers connect them to the entirety. Virtual routers are computer programs that drive information between databases.
If the system can morph the routes, that the information uses, that denies the computer stuck. In those intelligent systems, the routers, processors, and gates communicate with each other, forming the virtual neural network. And if there is some kind of problem. The system can choose another route for the information.
If there is more than only one processor in the system, the system can let the busy processor handle the problem. And route the next problem to other processors. The intelligent operating system can take complex problems to store if there are some busy things to do. And when it is completed the more urgent problem can return to that previous problem.
Image 2
The ability to remove problems from the memory and store them makes it possible to use the same computer for multiple tasks. The system can operate as human control in the daytime. When people are off the office, the system can handle complex problems. The ability to save data means that the system can stop some process and return to it later, without fear that the data is lost.
The virtual routers can operated by two or multi-layer AI-based systems. AI-based operating systems can make it possible to control complicated virtual database-based neural networks. AI-driven systems can also drive virtual quantum computers. In those systems, the computer selects multiple (as an example ten) data lines. Each of those data lines is an individual state of the virtual qubit. This kind of virtual system can put data travel in lines.
The best way to make that system is to use ten microprocessors. Then the system shares the data flow for each processor. That system makes it possible to improve the data handling capacity. Image 2 can portray a model of the virtual quantum computer that bases the neural network. If that system uses binary-sub architecture each ball is the microprocessor. The system sends data to the network, which cuts it into pieces. The system uses TCP/IP protocol and when it puts the serial number to each data segment, it can collect data back together.
The virtual neurons can make the systems more effective than they have ever been before. The virtual neurons require complicated programming algorithms. Handling those systems requires intelligent operating systems and intelligent complicated operating systems require powerful computers.
https://scitechdaily.com/supercharging-ai-with-new-computational-model-of-real-neurons/
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