Welcome to the forefront of conversational AI as we explore the fascinating world of AI chatbots in our dedicated blog series. Discover the latest advancements, applications, and strategies that propel the evolution of chatbot technology. From enhancing customer interactions to streamlining business processes, these articles delve into the innovative ways artificial intelligence is shaping the landscape of automated conversational agents. Whether you’re a business owner, developer, or simply intrigued by the future of interactive technology, join us on this journey to unravel the transformative power and endless possibilities of AI chatbots.

Lesson 1 of 22By Nikita Duggal

Artificial Intelligence (AI) has quickly moved from tech trend to everyday essential. We are seeing AI take on tasks like generating streaming recommendations, and supporting companies to analyze data more quickly. AI is reshaping the way we live and work. What was previously thought of as a science fiction plot is now quietly running in the background of daily life. According to McKinsey's latest report, AI is projected to add up to $4.4 trillion to the global economy annually, and its impact is set to grow even stronger. to the global economy every year, AI’s impact is only going to intensify.
In this tutorial, we’ll break down what AI really means, how it works, where it’s being used, and what makes it both exciting and challenging.

AI enables machines to think and act like us. Yes! Like humans. Imagine a computer or robot that can learn, reason, solve problems, and even understand language, just like we do. From recognizing patterns to making decisions, AI mimics the cognitive abilities of the human brain. 
By studying how we think and process information, AI systems are designed to think smarter and more efficiently, enabling them to perform tasks that once required human intelligence. Whether it's recommending your next favorite movie or driving a car autonomously, AI is shaping the future in ways we once only imagined.
Does this sound intriguing, making you wonder how AI accomplishes all of this? In the following part, we will learn how AI works, types of AI, and more. Let’s dig in. To explore AI further, check out this artificial intelligence tutorial.
Below are the various types of AI:
These machines do not have any memory or data to work with, specializing in just one field of work. For example, in a chess game, the machine observes the moves and makes the best possible decision to win. 
These machines collect previous data and continue adding it to their memory. They have enough memory or experience to make proper decisions, but memory is minimal. For example, this machine can suggest a restaurant based on the location data that has been gathered.
This kind of AI can understand thoughts and emotions, as well as interact socially. However, a machine based on this type is yet to be built. 
Self-aware machines are the future generation of these new technologies. They will be intelligent, sentient, and conscious.

AI systems work by merging large with intelligent, iterative processing algorithms. This combination allows AI to learn from patterns and features in the analyzed data. Each time an Artificial Intelligence system performs a round of data processing, it tests and measures its performance and uses the results to develop additional expertise.

(Image Source)
Now that you know how AI works at a basic level, let’s take a closer look at the two major categories of AI and how they differ in purpose and capabilities.
Next up in the what is AI discussion is weak and strong AI. When discussing artificial intelligence, it is common to distinguish between two broad categories: weak AI and strong AI. Let's explore the characteristics of each type:
Weak AI or Narrow AI, refers to AI systems that are designed to perform specific tasks and are limited to those tasks only. These AI systems excel at their designated functions but lack general intelligence. Examples of weak AI include voice assistants like Siri or Alexa, recommendation algorithms, and image recognition systems. Weak AI operates within predefined boundaries and cannot generalize beyond their specialized domain.
Strong AI, also known as general AI, refers to AI systems that possess human-level intelligence or even surpass human intelligence across a wide range of tasks. Strong AI would be capable of understanding, reasoning, learning, and applying knowledge to solve complex problems in a manner similar to human cognition. However, the development of strong AI is still largely theoretical and has not been achieved to date.
Let’s explore the following ways that explain how we can implement AI:
Machine learning gives AI the ability to learn. This is done by using algorithms to discover patterns and generate insights from the data it is exposed to. 
Deep learning, a subcategory of machine learning, allows AI to mimic a human brain’s neural network. It can make sense of patterns, noise, and sources of confusion in the data.
Consider an image shown below:

Here, we segregated the various kinds of images using deep learning. The machine goes through multiple features of photographs and distinguishes them with feature extraction. The machine segregates the features of each photo into different categories, such as landscape, portrait, or others. 
Let us understand how a deep learning model works. 
Consider the image shown below:

The above image depicts the three main layers of a neural network:
The images that we want to segregate go into the input layer. Arrows are drawn from the image on to the individual dots of the input layer. Each of the white dots in the yellow layer (input layer) are a pixel in the picture. These images fill the white dots in the input layer.
We should clearly know these three layers while going through this artificial intelligence tutorial.
The hidden layers are responsible for all our inputs' mathematical computations or feature extraction. In the above image, the layers shown in orange represent the hidden layers. The lines that are seen between these layers are called ‘weights’. Each one of them usually represents a float number, or a decimal number, which is multiplied by the value in the input layer. All the weights add up in the hidden layer. The dots in the hidden layer represent a value based on the sum of the weights. These values are then passed to the next hidden layer.
You may be wondering why there are multiple layers. The hidden layers function as alternatives to some degree. The more the hidden layers are, the more complex the data that goes in and what can be produced. The accuracy of the predicted output generally depends on the number of hidden layers present and the complexity of the data going in.
The output layer gives us segregated photos. Once the layer adds up all these weights being fed in, it'll determine if the picture is a portrait or a landscape.
Example – Predicting Airfare Costs
This prediction is based on various factors, including:
We begin with some historical data on ticket prices to train the machine. Once our machine is trained, we share new data that will predict the costs. Earlier, when we learned about four kinds of machines, we discussed machines with memory. Here, we talk about the memory only, and how it understands a pattern in the data and uses it to make predictions for the new prices as shown below:

Next up, in the what is artificial intelligence discussion is understanding how effective or helpful AI is truly! Artificial intelligence has pros and cons, much like any other innovation. Here’s a quick rundown of some pros and cons.
Let us continue this article on What is Artificial Intelligence by discussing the applications of AI.
Artificial intelligence (AI) has a wide range of applications across various industries and domains. Here are some notable applications of AI achieved using the latest and in-demand AI tools:
AI is used in NLP to analyze and understand human language. It powers applications such as speech recognition, machine translation, sentiment analysis, and virtual assistants like Siri and Alexa.
Artificial Intelligence techniques, including computer vision, enable the analysis and interpretation of images and videos. This finds application in facial recognition, object detection and tracking, content moderation, medical imaging, and autonomous vehicles.
AI plays a crucial role in robotics and automation systems. Robots equipped with AI algorithms can perform complex tasks in manufacturing, healthcare, logistics, and exploration. They can adapt to changing environments, learn from experience, and collaborate with humans.
AI-powered recommendation systems are used in e-commerce, streaming platforms, and social media to personalize user experiences. They analyze user preferences, behavior, and historical data to suggest relevant products, movies, music, or content.
Artificial Intelligence is extensively used in the finance industry for fraud detection, algorithmic trading, credit scoring, and risk assessment. Machine learning models can analyze vast amounts of financial data to identify patterns and make predictions.
AI applications in healthcare include disease diagnosis, medical imaging analysis, drug discovery, personalized medicine, and patient monitoring. AI can assist in identifying patterns in medical data and provide insights for better diagnosis and treatment.
AI-powered virtual assistants and chatbots interact with users, understand their queries, and provide relevant information or perform tasks. They are used in customer support, information retrieval, and personalized assistance.
AI algorithms are employed in gaming for creating realistic virtual characters, opponent behavior, and intelligent decision-making. AI is also used to optimize game graphics, physics simulations, and game testing.
AI enables the development of smart home systems that can automate tasks, control devices, and learn from user preferences. AI can enhance the functionality and efficiency of Internet of Things (IoT) devices and networks.
Artificial Intelligence helps detect and prevent cyber threats by analyzing network traffic, identifying anomalies, and predicting potential attacks. It can also enhance the security of systems and data through advanced threat detection and response mechanisms.
AI's reach doesn’t stop there. It’s being integrated into many other industries in creative and impactful ways. Let’s look at some real-world examples to see how AI is making a difference across fields.
AI tools have become an integral part of our everyday lives, revolutionizing various industries and enhancing user experiences. From sophisticated virtual assistants to streamlining repetitive tasks, AI is everywhere. Here are some extraordinary examples of AI applications:
ChatGPT along with other generative AI tools like Jasper AI, and Copy.ai, are revolutionizing content creation and communication. These AI models are designed to generate human-like text, which can be used for everything from customer service automation to generating creative content for marketing, education, and even software development. 
Google Maps utilizes AI algorithms to provide real-time navigation, traffic updates, and personalized recommendations. It analyzes vast amounts of data, including historical traffic patterns and user input, to suggest the fastest routes, estimate arrival times, and even predict traffic congestion.
Self-driving cars rely heavily on Artificial Intelligence AI for perception, decision-making, and control. Using a combination of sensors, cameras, and machine learning algorithms, these vehicles can detect objects, interpret traffic signs, and navigate complex road conditions autonomously, enhancing safety and efficiency on the roads. You can read more about autonomous self-driving cars here!
Tesla's Full Self-Driving Beta leverages AI for autonomous driving. It's an enhanced version of Tesla's Autopilot system, using neural networks and vast datasets from Tesla's fleet of cars. FSD makes real-time decisions, navigating complex city environments, including stopping at traffic signals, recognizing pedestrians, and handling lane changes.
Both Netflix and Spotify use AI to recommend personalized content based on user preferences. These platforms analyze past behavior, viewing habits, and listening patterns to suggest movies, shows, and music tailored to each user's tastes. This has greatly enhanced the user experience by providing highly relevant recommendations.
Getting an Artificial Intelligence certification can open up numerous opportunities, especially as AI revolutionizes various industries. Here's why you should consider it:
1. Scale Up Your Career: As AI continues to transform various sectors, having a certification ensures your skills align with industry needs. A report by McKinsey indicates that 92% of companies plan to increase their AI investments, underscoring the growing importance of AI competencies.
2. Increase Your Earning Potential: Professionals with AI expertise often enjoy higher earning potential. ZipRecruiter reports that AI engineers earn over $101,000 per year. Moreover, Glassdoor indicates that the average compensation for AI Engineers in the U.S. is over $205,000. These figures highlight the lucrative opportunities available for professionals with AI expertise.
3. Gain Networking Opportunities: An AI certification often provides access to a network of professionals and experts, facilitating collaborations and opening doors to new career opportunities within the AI community.
Organizations are adopting AI and budgeting for certified professionals in the field, thus creating a growing demand for trained and certified professionals. As this emerging field continues to grow, it will impact everyday life and lead to considerable implications for many industries.
If you wish to master AI, you must explore and enroll in the Professional Certificate in AI and Machine Learning, delivered in collaboration with Purdue University Online, Simplilearn, and IBM. This program will help you gain industry-level expertise in trending topics such as AI automation, ChatGPT, agentic frameworks, and so much more. Join today!

Artificial Intelligence in simple words refers to the ability of machines or computer systems to perform tasks that typically require human intelligence.
The current categorization system categorizes AI into four basic categories: reactive, theory of mind, limited memory, and self-aware.
The main goal of AI is to create systems that can think, learn, and solve problems like humans.
AI is a tool. It can be good or bad depending on how it's used. When used responsibly, it can help improve lives and solve big problems.
Aside from planning for a future with super-intelligent computers, artificial intelligence in its current state might already offer problems.
The advantages of AI include reducing the time it takes to complete a task, reducing the cost of previously done activities, continuously and without interruption, with no downtime, and improving the capacities of people with disabilities.
Nikita Duggal is a passionate digital marketer with a major in English language and literature, a word connoisseur who loves writing about raging technologies, digital marketing, and career conundrums.
Professional Certificate in AI and Machine Learning
Applied Generative AI Specialization
Microsoft AI Engineer Program
*Lifetime access to high-quality, self-paced e-learning content.
How Does AI Work
Artificial Intelligence Career Guide: A Comprehensive Playbook to Becoming an AI Expert
What is Artificial Intelligence and Why Gain AI Certification
Types of Artificial Intelligence
What is ChatGPT AI and Why Does it Matter?
Introduction to Artificial Intelligence: A Beginner's Guide
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