AI for Beginners: Understanding the Basics of Artificial Intelligence

 Ai For Beginners: Understanding The Basics Of Artificial Intelligence

Our world is experiencing a rapid evolution of technology, and it is in this evolution that we encounter the controversial term, Artificial Intelligence (AI). AI has become one of the most discussed topics of the century, with its remarkable capabilities and unique advantages being analyzed all around the world. But what is AI? AI is at the forefront of technological advancement and is the backbone of many machines and devices that we use these days.

What is AI?

AI, or Artificial Intelligence, is the simulation of human intelligence in machines designed to perform tasks that would otherwise require human intelligence, such as learning and problem-solving. AI refers to intelligent machines that are programmed to complete a specific task with efficiency. The first-ever use of AI dates back to the late 1800s, where machines capable of statistical analysis and computation were developed. AI has come a long way, and we now have AI-powered machines in different industries, including healthcare, education, and finance. AI has revolutionized the way businesses operate and brought a positive impact on the world.

Practically anything that could be perceived by a machine as a pattern could be trained for AI machines to learn. For instance, if you go on YouTube and watch videos on cooking, machines can identify it as a pattern and utilize this for AI. In other words, AI shows the possibility of a universe of technologies that could enhance human progress and life, and do all the things we need them to do.

AI is classified into two categories: Narrow AI and General AI. Narrow AI refers to the AI designed to perform specific tasks, such as collecting data and recognizing patterns. It is the most common form of AI. Whereas, General AI refers to the AI that can complete any intellectual task that a human being can perform. It is usually called artificial general intelligence and could surpass human intelligence.

Applications of AI

AI has found its application in an array of industries from education, healthcare to manufacturing, and finance. Here are some examples:

Medicine and Healthcare:

AI is playing a vital role in healthcare. AI-powered devices like Fitbits can record vital signs like heartbeat and calories burnt throughout the day. AI tools can help in the early detection of diseases like cancer and provide treatment options to healthcare specialists. AI systems can also analyze electronic medical records and assist medical practitioners with diagnoses and treatment plans.


In the manufacturing industry, robots are increasingly being used to perform tasks such as welding and painting the car parts, and even assembling electronic gadgets. AI has made the robots much quicker and more efficient than human beings and have improved the overall functioning of the manufacturing industry.


AI can personalize learning by a process called adaptive learning. It allows the computer to analyze the learning pace of the student and adjust the content delivery based on those needs. This ensures that the student receives information when they are ready for it.


AI technology is useful in marketing by analyzing data that could be used to create marketing campaigns. It also aids in identifying the target audience of specific ads and measuring ad performance.

How AI Works?

AI works by using algorithms that input data into a set of AI models that will output a response. It works through these simple steps:

1. Data Preparation:

AI models require data to function properly. Before the AI system can examine data, the data must be preprocessed to ensure accuracy. The data is cleaned, hierarchically arranged, missing values filled in, transformed to useful features for the AI, and forwarded for analysis.

2. Training Data:

The AI system learns over time. For the AI model to learn, it must be trained with relevant data. The training data must contain visible inputs and the desired outcomes referred to as labeled datasets.

3. Algorithms:

The AI system utilizes different algorithms to process the data inputted into it. Plenty of algorithms that work on a variety of AI applications are available. Some of the most commonly used algorithms for AI include decision trees, neural networks, reinforcement learning algorithms, and k-means clustering.

4. Testing:

After training with the datasets, the AI model’s performance is tested with new sets of inputs. By doing this, the AI model can be evaluated for its accuracy and performance, followed by fixing the bugs and updating it.

Challenges of AI

Although AI holds a vast potential for solving problems and making life easier, it presents several challenges, such as:

Job Losses:

AI undoubtedly has the potential to replace many jobs that are currently being done by humans. Robots can perform repetitive tasks much faster than human beings can. This may lead to job losses in the future.

Ethical Issues:

AI decision-making algorithms may be biased towards certain groups of people, leading to issues around the ethics of AI. For instance, AI algorithms could be used for predictive policing based on race, leading to discrimination.


AI is a double-edged sword when it comes to cybersecurity. It can be used to strengthen the security of systems or used by hackers to commit cybercrime.


In conclusion, AI is powering the computing technology of the future, and it’s in our best interest to understand and use it. With the advancements in machine learning and the development of more complex algorithms, we will see AI being integrated into more areas of our lives. Nonetheless, there are challenges that come with AI, and we must consider these challenges as we develop policies that address these challenges to foster widespread adoption of AI across different industries.

Thank you for reading and see you again in another interesting article.

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