Artificial Intelligence (AI) and Artificial Neural Networks (ANN):

Artificial intelligence is a branch of computer science in which intelligent machines are created or designed which has the ability of learning, planning(reasoning) and problem solving(self-correction).AI is the simulation of human brain (human intelligence)implanted in machines ,especially in computer sciences. Most of the AI designed machine has the ability to identify patterns in different input and there action (output) d depend upon the recognized pattern of their input. Generally AI machine or software are train through different techniques like Heuristics, Support Vector Machines, Neural Networks, the Markov Decision Process, and Natural Language Processing. All these techniques servers in different disciplines such as Computer Science, Biology, Psychology, Linguistics, Mathematics, and Engineering.

Artificial Neural Networks (ANN) is an evaluation model based on the ability of human brain to learn and interoperate the data. ANN is composed of different hidden layers and these hidden layers are present between the input and output just like the neurons present in human brain which process the input data from human senses and define our action on these input. In ANN these hidden layers are called activation functions. The working of activation function is to find or make the pattern between the input and output, all this process is called the training of ANN. The more data given to ANN the better the efficiency of ANN. Sometimes the ANN become over efficient which is not desirable. The application of ANN is very vast and this field is the emerging one. ANN application covers almost every field of sciences like

Aerospace − Autopilot aircrafts, aircraft fault detection. Medical − Cancer cell analysis, EEG and ECG analysis, prosthetic design, transplant time optimizer.
Automotive − Automobile guidance systems. Control − ANNs are often used to make steering decisions of physical vehicles.
Military − Weapon orientation and steering, target tracking, object discrimination, facial recognition, signal/image identification. Time Series Prediction − ANNs are used to make predictions on stocks and natural calamities.
Electronics − Code sequence prediction, IC chip layout, chip failure analysis, machine vision, voice synthesis. Software − Pattern Recognition in facial recognition, optical character recognition, etc.
Transportation − Truck Brake system diagnosis, vehicle scheduling, routing systems.


Speech − Speech recognition, speech classification, text to speech conversion.


Anomaly Detection − As ANNs are expert at recognizing patterns, they can also be trained to generate an output when something unusual occurs that misfits the pattern. Financial − Real estate appraisal, loan advisor, mortgage screening, corporate bond rating, portfolio trading program, corporate financial analysis, currency value prediction, document readers, credit application evaluators
Signal Processing − Neural networks can be trained to process an audio signal and filter it appropriately in the hearing aids. Telecommunications − Image and data compression, automated information services, real-time spoken language translation.
Telecommunications − Image and data compression, automated information services, real-time spoken language translation.

Article written by  USAMA MAHMOOD