How Artificial Neural Network Could Modify AI
The artificial neural network is a multi-interconnection computable system distinctly inspired by the biological neural networks that make-up animal brains.
The biological artificial system of this nature learns to perform tasks by considering examples generally without any specific-task program rules.
In other words, the system made of artificial neural networks can perform multiple tasks that were not specifically written as a program in it. It is a unique internetworking of the neural system artificially.
A typical ANN is a mimicking technology of animal brains. Ideally, the ANN system can perform virtually anything actual animal brains can perform but this claim is yet to be proven practically.
The ANN is believed to use an image recognition system to learn how to identify images.
For instance, a previous image of a cat drawn on a wall or paper can be saved by the ANN brains system at its various sizes and the data stored will be used to detect any physical cat walking on the street or any cat images on papers and walls.
The future machines to be built with the artificial neural network (ANN) will not only become an advanced Artificial intelligence machine.
But rather they can actually teach humans special knowledge and skills.
This ability to teach can be possible because they actually acquire the knowledge without a written program instead the ANN systems will be learning skills, environment analysis, behaviors, and vocals of the humans by visually looking at and storing whatever they see humans doing.
The ability to repeat what they saw humans do without any command or programming will make them super-machines that humans should be afraid of.
If the artificial neural network will be incorporated into artificial intelligence machines such as humanoid robots, Animatronic robots, autonomous vehicles like drones, etc.
Then their operations within the environment and industrial sector will become a concern to the developers as such future technology may have numerous advantages as well as numerous disadvantages.
However, the good thing about such technology is that future machines of such nature could be thought the laws of humans which include all the Dos and Don’ts.
Technically, when it comes to the principle of operation, the artificial neural network is an interconnected group of nodes, akin to the vast network of neurons in a brain.
In it, each circular node represents a connection between the output of one artificial neuron to the output of another.
In other words, An Artificial neuron network is based on a collection of connected units or nodes called the artificial neurons which loosely model the neurons in a biological brain.
Based on the original goal of making the system able to solve problems as human brains would do, a lot had been committed to seeing how successful the idea would be.
In the artificial neurons, each connection is like the synapses in a biological brain and can transmit a signal from one artificial neuron to another with each artificial neuron having the ability to process each signal independently and signal the result to the next artificial neuron connected to it, just as the human brain does.
The signal at a connection between artificial neurons is a real number, and the output of each artificial neuron is computed by some non-linear function of the sum of its inputs.
The connections between artificial neurons are called ‘edges’. Artificial neurons and edges typically have a weight that adjusts as learning proceeds.
The weight increases or decreases the strength of the signal at a connection. Artificial neurons may have a threshold such that the signal is only sent if the aggregate signal crosses that threshold.
Typically, artificial neurons are aggregated into layers. Different layers may perform different kinds of transformations on their inputs.
Signals travel from the first layer (the input layer), to the last layer (the output layer), possibly after traversing the layers multiple times.
The artificial neurons play important roles in the entire Artificial Neutral Network (ANN) working process.
With more inventions and discoveries such a system would replace the current method of operations of Artificial intelligence machines.
Instead of programming, visual learning and human teaching may become the model of future machines.
