Theoretically creating the artificial brain is easier than people imagine. The only needed thing is the network of wires some springs connect certain connections when those connections are needed. The system requires the iron wire and then there must be springs at the end of each iron wire. Those springs connect circles anytime when that connection is required.
The system can use a copper or like in the example case silver cable that is connected to a brush-shaped structure. And at the end of each wire in the brush is an independently operating spring that connects two wires. When that connection is needed. In some versions those wires are connected with miniature ion or cathode cannons that send the electron burst to the receiver. Those springs can be those electron cannons.
"Scientists have demonstrated that nanowire networks can exhibit short- and long-term memory, similar to the human brain. These networks, comprised of highly conductive silver wires covered in plastic and arranged in a mesh-like pattern, mimic the physical structure of the human brain. The team successfully tested the nanowire network’s memory capabilities using a task similar to human psychology experiments". (ScitechDaily.com/Neural Nanotechnology: Nanowire Networks Learn and Remember Like a Human Brain)
"This breakthrough in nanotechnology suggests that non-biological hardware systems could potentially replicate brain-like learning and memory, and has numerous real-world applications, such as improving robotics and sensor devices in unpredictable environments." (ScitechDaily.com/Neural Nanotechnology: Nanowire Networks Learn and Remember Like a Human Brain)
Image 2) Axons look like flowers. Every "flower" in the axon is the receiver or transmitter that transmits neurotransmitters. I didn't find an electron microscope image of the axon, so I must use the image of the flower to demonstrate how the neuron emulates the qubit. When one receiver-transmitter pair makes contact, the neuron that acts like a qubit gets value 2. The reason for that is that the qubit's first two values 0 and 1 are reserved to tell the system if it is on or off. And the calculation of those states begins always from zero.
In that model, electrons act as neurotransmitters. And the brush-shaped structures are like qubits.
When we are looking carefully at the synapsis of the axons, we can see a group of structures that are looking like a group of flower-looking transmitter-receivers. If we think that the neurons act like qubits the number of those "flowers" that are making the connections can determine the state of the qubit in those cells.
If one of them makes a connection the value of the qubit means it's on. And if three make the connection with another neuron, the qubit has two free states. The linear information model means that the first thing that travels between qubits adjusts the receiver to value one. Then the system sends the message to the receiver.
The new nanonetwork can learn and remember things like the human brain. This nanonetwork has two types of memories. Short- and long-term. And that nanowire construction can be the next-generation tool for making learning systems. Those kinds of neural networks, there is no need for microchips are a thing that emulates neurons.
But the structure that base is in the programmable energy barriers and triggers that can release energy when the right signal comes makes it possible to create new nano- or why not, larger scale robots that learn their missions like humans. The idea of the structure is taken from ultra-tunable bistable structures that Chinese developers created. The bistable structures can act like neurons. And that thing makes it possible to create nano-structures that act like neurons.
https://scitechdaily.com/shape-shifting-structures-the-future-of-robotic-innovation/
https://scitechdaily.com/neural-nanotechnology-nanowire-networks-learn-and-remember-like-a-human-brain/
Comments
Post a Comment