Artificial Intelligence is now present in many spheres of our life. This rise of AI is both exciting and challenging because AI and machine learning have become an inseparable part of our life. The easiest way to understand artificial intelligence is to map it to something that we already understand, i.e. our intelligence. You can undertake this approach when you avail a course to study artificial intelligence. Human intelligence, at its most basic level, follows a simple progression. It takes information, processes it, and then uses that information to help us act.

Human Intelligence

To help you understand the process, human intelligence has three general steps. These steps are input, processing, and output.

INPUT

In the human brain, an input is received by  sensing or perceiving things.

PROCESSING

Your senses like your eyes, nose, ears etc., aid in this process.

OUTPUT

Your brain then processes the information and produces the output.

This output can be in the form of speech or action, both of which are dependent on how the raw information is perceived by our brain.

For example, picture yourself stopping at an intersection.  Your eyes will see that the traffic light in front has just turned green. Based on what you have been taught in your driver’s education and from experience, you know that green light indicates that you should drive. The green light is the raw information, while putting the car in motion is the output. Everything else in between is processing.

To intelligently work around the world, like answering the phone, baking or obeying traffic lights, we need to process the input that we receive. This is the main feature of human intelligence processing, which can ultimately be broken down into three different aspects: –

• Knowledge and memory:

We build up knowledge by learning facts, and by adhering to social norms, like saying ‘please’ and ‘thank you’. At the same time, our memory allows us to recall and apply information from the past to present situations.

• Decision and inference:

Decisions and inferences made on raw information are combined with knowledge and memory.

• Learning:

Humans can learn by example, observation or algorithm. When we learn by example, we are told that one animal is a dog while the other is a cat. Learning by observation allows us to figure out on our own that ‘dogs will bark’ and ‘cats will meow’. The algorithm, which is the third learning method, allows us to complete a task followed by a series of steps or a specific algorithm.

The above-mentioned aspects of human intelligence are parallel to artificial intelligence. Just like we take information, process it and share the output, so do machines. You can learn more about the process by taking up artificial intelligence training online.

Artificial Intelligence

In AI and machine learning, the input part of artificial intelligence is exemplified by speech recognition, natural language processing, visual recognition and more. You see AI and machine learning technologies are everywhere, right from self-driven cars that need to sense the oncoming obstacles, to Alexa or Siri that recognises your speech. The output produced by the machines is the way it interacts with the world around us. This might be in the form of navigation systems, speech generation, etc. In between, different forms of processing are taking place.

Similar to our accumulation of knowledge and memories, machines too can create knowledge representations or databases that help them store information about the world. Just as we make decisions and draw inferences, the machines too make predictions, optimise for targets, and determine the next steps or decisions.

Lastly, just as we learn by example and observation, machines too can be taught using analogous methods. Machine learning courses online will teach you the different ways in which AI and machine learning works.

How do machines learn?

By Example

One of the ways machines learn is by example. The computer is given a dataset along with labels within a data set that will act as answers. The machine eventually learns to tell the difference between labels.

Unsupervised

The other type of machine learning you will learn about during your study of artificial intelligence is unsupervised machine learning. This learning is by observation. The computer observes patterns and learns to differentiate between groups and patterns on its own. This type of learning doesn’t require labels, and is preferable when data sets are limited or do not have labels.

Through Algorithms

The third way by which a machine learns is through algorithms. Here, the programmer instructs the computer exactly what to do, line-by-line. In common speak, this is called a software program.

Ideally, to get the most accurate and efficient artificial intelligence results, the machine will need to get a combination of learning methods. Both supervised and unsupervised methods of machine learning are useful; it is all about using the right approach to the right case. In that regard, a focused course in artificial intelligence online can teach and imbibe in you the best machine learning techniques to apply for different cases.