These would include learning by taking in information and rules for using the information — reasoning which is using those rules to reach a proper conclusion or to reach the purpose of the AI itself and self-corrective actions. It is the new ERA of modern-day computing. With AI plugged in, people would be able to leave their offices to have their computer do much of their work for them.
There are many types of AI which are categorized and here are two examples.
• Weak AI- these is the AIs that are also known as narrow AI. And they are designed and made only for a particular program. They are usually used as personal assistance and have a fixed amount of data and information it can use to give the user.
Example- SIRI from APPLE and CORTANA from WINDOWS
• Strong AI- this is known as the Artificial General Intelligence. This is an AI with Human abilities which are cognitive. This means that when there is a given task which is out of bounds of what it usually has learned or knows, it must use the information it has to provide a feasible solution. To find out whether an AI is capable of being an “AI,” the Turing test was made by Alan Turing in 1950. This is a test which is used to find out whether a computer can think like a human.
AI can be used for a wide variety of things. Here are some examples
• Automation- this is what makes a system or a simple service or a process in general fully automatic.. it can be programmed in such a way that it would be able to produce the highest amount when it comes to production output and value than what would usually be done by humans.
• Machine learning- this is where AI gets strong. In this type of Ai, the computer would program itself to achieve a specific goal. It can give a very predictive analysis of what all can be used to make the said goal
Supervises learning; this is where the patterns are labeled so that new sets of data is learned
Unsupervised learning; this is where the models aren’t marked so that the data is sorted according to the similarities and dissimilarities
Reinforcement learning; there are no marked, but the AI performs a task many times over and gives back feedback.
• Machine vision: the science of letting the computers see. This involves using computers and technology like sensors to be used as eyes. With the information which they receive which is ten times more than what the normal human eye receives because of the infrared thermal scans and X-rays, their won’t be any biological deterrence that comes in the way.