Woahhh… Surprised that I’m gonna cover every facet of Artificial Intelligence in only a single blog post!? That’s definitely unattainable!! But, I’m sure I can provide you with a fundamental grasp of it through this blog.

Most of our routines start with unlocking a phone using the fingerprint or facial unlock options and eventually finally ends up with, “Amazing!! I made it to 10,000 steps today” or “Hey Siri, set the alarm for five a.m.” Whether we prefer it or not, we spend a major period of time interacting with smart systems, and it’s (AI) becoming an important a part of our modern existence. From Search engines like google and yahoo to Virtual Assistants, Recommender systems, Google maps, smart homes so on.. Using mathematics and algorithmic techniques, AI solves these complex real-world problems.

Artificial Intelligence is a science that develops theories and methodologies to make machines which can be able to pondering and understanding the world intelligently, in addition to reacting appropriately to the situation in the identical way humans can do. AI is closely related to review of human brain. We would like our machines to sense, reason, think and act. We will create a machine that’s able to learning, pondering, and acting in the identical ways in which the human brain does. This might be used as a platform for developing intelligent learning systems.

Although being excellent at understanding the world around us, the human brain is unable to process the unstructured, unmanageable, and chaotic volumes of information that’s being produced daily. Because of this, we must create intelligent machines which can be able to handling massive amounts of information efficiently, indexing and organizing the info in a way that enables us to attract conclusions, learning from latest data and updating always using the suitable learning algorithms, think and react to situations based on the circumstances in real time.

Applications of AI

Let’s see how AI is helpful in various domains and has been used across many industries.

It deals with visual data similar to images and videos. For instance, these systems/algorithms can analyze medical images to assist diagnose diseases, monitor patient progress and guide treatments, can analyze video footage in real-time to detect potential security threats etc.

These systems enables human-computer interaction.

“Alexa! play Baby Baby Baby oh..”

• Can capable of hear and tries to know what we’re asking it and converts the speech to text.
• Does lexical, syntactic and semantic evaluation of text to find out the meaning of a sentence.
• Super cool…!! Song is already being played. Are you able to listen it!?

Remember ChatGPT 🖤

Have you ever ever tried playing chess or AlphaGo with a pc? If not, give it a shot instantly and see how smart the system is playing. It’s all a part of the AI magic.

A knowledge-based system that uses knowledge about its application domain and uses an inferencing procedure to unravel complex real-world problems. Expert systems use a knowledge base of a specific domain and produce that knowledge to bear on the facts of the actual situation at hand.

Just about all the e-commerce industries are surviving using this advice system. Ever pondered how, after placing an item in our shopping cart, similar items that other customers have purchased can even get displayed (Customers who bought this item also bought XXXXX).

Constructing an intelligent System

Some of the commonly used techniques for constructing an intelligent system includes . Here, We impart intelligence to an agent through data and training.

AI assistants, similar to Alexa and Siri, are examples of intelligent agents because they use sensors to discern a user’s request and robotically collect data from the web without the user’s assistance. Once after the sensor perceives the input, it sends it to the feature extractor to get all of the relevant features. Now the pre-trained ML model (inference engine) make predictions based on the training model. The choice taken by the inference engine is then sent to the actuators, which then takes the corresponding motion in the actual world.

To be able to understand machine learning and construct a whole solution, one must be acquainted with many techniques from different fields similar to pattern recognition, artificial neural networks, data mining, statistics, and so forth. Among the best parts is that we don’t must work out the underlying mathematical formula. Because machine itself derives the formula from data, you don’t must know complex mathematics. All we want to do is create the list of inputs and the corresponding outputs. The learned model that we get is just the connection between labeled inputs and the specified outputs.

Here comes the tip…!! We learned what AI is all about and why we want to review it. We discussed various applications, discussed learn how to develop an intelligent agent using machine learning.

Let’s deep dive into Artificial Intelligence within the upcoming blogs. Till then,