Artificial Intelligence: Revolutionizing the World

Mohammad-Hussein-DewjiThe writer, Mohammad Hussein Dewji (Dar es Salaam, Tanzania) a tech and AI enthusiast with over a decade of coding experience. He has had the privilege of working with FAANG companies, where he has been exposed to cutting-edge technologies and collaborated with brilliant minds. Mohammad is passionate about transforming ideas into efficient software solutions and leveraging AI to tackle real-world challenges. Constantly learning and staying up-to-date, he strives to make a positive impact merging Tech, AI and today’s world.

Artificial Intelligence


rtificial intelligence (AI) has emerged as a transformative force, reshaping industries and our daily lives. Its ability to process massive amounts of data, recognize patterns, and make decisions has captivated our imagination, evoking a mixture of excitement, fear, and confusion. To fully grasp AI’s nature, let’s first explore its definition.

According to Google, AI is defined as “intelligence demonstrated by computers, as opposed to human or animal intelligence.” However, this definition only scratches the surface. True intelligence encompasses a wide range of cognitive abilities, including logic, understanding, self-awareness, learning, emotional knowledge, reasoning, planning, creativity, critical thinking, and problem-solving. While AI has made impressive progress, it has not yet reached the level of human intelligence.

AI operates by undergoing a training process where it learns from a vast amount of data. This training phase can span weeks to months, as the AI system gradually acquires knowledge and patterns from the data it is exposed to. Some argue that AI can be self-taught on the job, but it still relies on correct information to understand and function effectively which requires constant data and monitoring. With this in mind, It is important to remember that AI should be seen as a tool rather than a replacement for human labour. While AI can enhance accuracy and reduce errors, it is still in its developmental stage and has limitations.

However, how does this entire process work? How does the AI understand this data and implement it to achieve the best possible result? The answer is very simple: Patterns and Probability. For artificial intelligence to be at its best it is necessary for it to have 2 things, the first of it being data and the second, a neural network which is also the building blocks for AI as well as the brain.

We constantly hear the phrase, data is the currency of tomorrow. The reason for that is that data has consistently proven to give humans an edge and insight in several situations. Let’s take for instance after a person goes through physical trauma, in this case, any medical personnel will first look at the cause of trauma, ‘was the patient hit by a car’, ‘ Did he drown in a swimming pool’, ‘Was he attacked by a blunt or sharp object’. Throughout this process, data is given about the condition of the patient, once the data has been acquired professionals begin to process this data to analyze the patterns from their own experience and knowledge then make conclusions on the probability of what has been damaged and the best course of action. We can take another scenario that all of us have experienced, texting a friend. From the moment you text that first hello, your mind is set on gathering data. If you try it even while reading this, you will notice your mind will begin to ask questions after that first text such as “Is this a good time to text?” or “What would the mood of this person be?” or even “I wonder if they will see my text?” while these seem natural they set a tone for the conversation, and lead us back to looking through what we know about the person (Data), finding the pattern based on the data we have of said person (Time Zones, Recent Events, Interactions) to come to probabilities as conclusions (Time, Mood, their likeness of you). We could go on and on, but at its essence, as humans, we have been created to gather data, analyze the patterns and take a course of action, and that is exactly what artificial intelligence does. 

Computers have the ability to analyze data at faster speeds than the human mind. While the human mind tends to take shortcuts, sometimes ignoring data to come to a conclusion quicker, computers are bound to run entire simulations for all scenarios taking into account all the data it has been provided and generate a probability on the best course of action resulting in a slight delay but more accuracy. To come to these conclusions, AI uses neural networks. A neural network consists of 2 parts: the neuron and the node. The neuron is represented by a circle in a diagram, while a node is a line between neurons together they give you a neural network. When we take another step back we find that neural networks also have 3 layers: The input layer, where the data is put in, the hidden layers (These can be multiple), which look for specific features and assigns probabilities, and the output layer, which is the result. 

Before data moves through the network, it is divided into subsets. As it progresses from the input layer to the first hidden layer, each subset is analyzed by neurons to identify patterns related to specific features. The neurons perform mathematical functions to calculate the probabilities of these features based on the subset of data being analyzed. The probabilities are then assigned to the connecting nodes, linking the neuron to the next layer. Once the data has passed through the entire hidden layer, the AI system reaches a conclusion by selecting the path with the highest probability.

In its essence, Artificial Intelligence is a computer that has access to data or is collecting data, then is taking steps towards analyzing this data to find patterns that are crucial towards its task and it has been programmed to look for and lastly feed this data through a neural network to generate a set of probabilities that lead to output whether this is a prediction of what’s most likely the next word, or even classifying anomalies in an x-ray through the RGB values in an image.

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