How is AI technology made and how does it work?

Artificial intelligence (AI) is the process of infusing human intelligence into machines to enable them to think like humans. To understand this technology easily, you need to know how artificial intelligence (AI) works.

In fact, AI is a field of computer science that uses the human mind. An AI system does not run by itself; it has to be fed with data, i.e., information and data, which is a kind of ‘data source’. And the AI system processes it. It builds a model from the way it is initially trained, produces results based on data, and interacts with or mimics the human mind. The more data is fed into the AI, the better it becomes. But not all AI systems require large data sources. Especially ‘big data’ is a very important aspect of AI. AI requires four main processes to work: machine learning, neural networks, data and data processing, and algorithms.

Machine learning (ML) is called the foundation of AI. It simply means teaching machines how the human mind works. For this, as much data as is entered into the machine learning tool and an AI system, a data set is built from it.

The AI system learns from data through the process of machine learning. But in order to process the data, software programmes and algorithms are needed to extract useful information from the data. Now there is so much data that it can be called a pyramid of data. A mathematical model is needed to process this data. ‘Image classification’ is an example of this. As you go to some websites, you are asked to choose from among many photos that show traffic lights. Identify the cat in the photo. How does the system know if you have selected the right photo or not? Yes, this is machine learning.

Another important part of AI is the neural network, which is also known as the ‘building blocks of AI’. Especially machine learning of AI system is due to neural network. Which is a neural network architecture inspired by biology. Just as the neurones of the human brain are interconnected, there are many types of hidden layers in the neural network. Data processing takes place by passing through those layers. As the data passes through the layers, it enters the deep learning stage of the machine. By connecting all the connections in the data, the AI system gives good results.

Its method is as follows:

First, the input layer receives the data. The hidden layer processes the data. Finally, the result is obtained through the output layer. The most important thing for artificial intelligence is data. Data is also called ‘Fuel for AI Systems’. Because without a data set to train an AI model, nothing can be done. Such a data set needs to have many types of characteristics. As the data should be complete, no data should be missing. Data continuity is also required for AI systems to work. The data should be accurate and factual. It should not contain any incorrect data. Also, the data should be updated. Generally, three types of data input should be given to train an AI system, i.e., structured, unstructured, and semi-structured data.

Structured data includes dates, locations, credit card numbers, number series, or other standard input methods. In structured data, data is always in a standard format.

In unstructured data, any specific data or information is lost. The AI system tries to find patterns in unstructured text, photos, and videos. For this, the AI system processes data through NLP (natural language processing), computer vision, or other methods.

Since AI systems do not have any pre-defined models, semi-structured data is used. In this way, the data uses ‘JSON’, ‘XML’, and ‘CSV’ formats. By adopting this method, it is possible to take advantage of the unstructured data source, and it is easy to store the data obtained for training.

Algorithms are the last important part of artificial intelligence. Algorithms are also called the ‘backbone’ of AI. Algorithms, in particular, are mathematical processes that describe how AI systems learn, improve decision-making, and manage problem-solving. The algorithm itself transforms the raw data into useful data, and the customer’s and the business’s efforts are what make it happen.

Now that you understand how an AI system works, let’s look at some real-life examples of it. The advancements made in technology are all around human life. People have started using devices, technologies, and systems with new types of AI features, from normal technology to new ones, from morning to night. Moreover, human life is becoming easier and affected by the use of technology with AI features.

As soon as we wake up from sleep, we rush to check social media updates on our smart phones. Some people open their mobiles by biometric unlocking and others by Face ID. If you have an Apple brand mobile and it opens with Face ID, Apple’s Face ID has ‘3D’ technology. Which places 30,000 ‘infrared dots’ on your face and takes your photo. Then the machine learning algorithm compares the data stored on your photo on the mobile, determines whether the face being scanned matches your face or not, and decides whether to open the mobile or not. Apple says its Face ID technology is so strong that it has a one in a million chance of fooling him.

After unlocking your phone, whenever you go to a social media platform, you check the notifications and updates that have come through overnight. Here, AI is sitting in the background and working. Filters what to show you and presents it to your screen. Because the AI system knows what you like to see based on your surfing habits (website and social networking habits), search results, shopping, your routine posts and photos, voice commands, location, etc. Friend recommendations, shopping advice, dining options, and news updates are sent to you based on your past activity. Not only this, AI’s machine learning technology is also working to protect you from false news and cyber bullying.

As soon as we reach the office every day, our job is to check the email. Your system may have ‘Grammarly’ or another spell-checking tool activated. These spell-checking tools work to make sure that you don’t make mistakes in your email or in the correctness of your sentences. For this, these tools use AI and natural language processing. In addition to receiving emails in your inbox, AI is also being activated to filter spam messages.

Suspicious spam is identified and blocked. In fact, even installed antivirus software protects your email using machine learning methods. Even to check whether our system has an internet connection or not, we type Google in the address bar, and not a day goes by without us doing a Google search. In our search command, Google searches the entire internet and gives the correct results. This is possible because of AI. Additionally, AI itself activates the advertisements that we see on any website, blog, or YouTube channel.

If you are spending time watching a long video, then AI will understand that you must watch that video, and ads will appear on it. For example, if you are searching for a company’s website to learn about it and you reach its YouTube channel, the YouTube channel has fewer subscribers, but the video shows an advertisement. Because you stop there for a while to get information. At the same time, AI understands and tries to take full advantage of that.

Now it’s time for smart home devices. Our home is getting smarter day by day. Nowadays, devices with voice commands, sensor lights, and automatic temperature balancing systems have started to be used in the home. The smart refrigerator gives a list of foods that are spoiling in the refrigerator and foods that need to be added. These are all “IoT” (Internet of Things) devices, which use AI.

If you use a platform like Amazon for shopping, its AI algorithm knows what you and other people like. Recommends products to you based on that. If we download any app, it asks for access to the microphone, gallery, and contact, and we give it access. If you screw up your earphones, that will be transmitted to the app through the phone’s mic. From there, the data is filtered and goes to the company’s shopping website. On your shopping website, AI recommends any product that it deems appropriate.

You start watching web series or movies on the OTT platform to get rid of the tiredness of working all day. Now that you have opened Netflix, the company’s ‘Artificial Intelligence Supported Recommendation Engine’ will recommend you watch more movies or web series of the same type based on the movies or web series you have watched before in the app.

AI is often in charge of, helping with, or making decisions in our daily lives. Artificial intelligence requires four major processes to work. which machine learning has been discussed some time ago. Now let’s understand it in detail.

There are many self-teaching programmes for teaching machines, which are based on three basic machine learning methods: unsupervised learning, supervised learning, and reinforcement learning. To explain this, we are giving an example of the outbreak of the coronavirus. When COVID-19 was at its peak, researchers accessed data sets linked to the medical profiles of thousands of patients to develop a vaccine.

For this, the protein that the virus was made of was investigated. Like spike protein. Researching this and producing a vaccine was an important role of AI. An AI system studies such a complex structure, analyses thousands and millions of components, and searches for one. Which is capable of developing immunity in the human body. In order to continue making the vaccine over time, the AI system keeps looking for such components, which have no possibility of being mutated or changed. This is possible through computational analysis and machine learning algorithms.

From the AI system itself, vaccine researchers get data insight, and it becomes easy to study whether the virus is mutated or not in the near future. This again requires big data or data sources, which are obtained from thousands of experimental or real sources. There was no shortage of such data during the COVID-19 pandemic, as the entire world was in the grip of the Corona virus. In 2019, the National Institute of Allergy and Infectious Diseases conducted the first clinical trial of an AI-based flu vaccine in America.

Then scientists from Flinders University made a vaccine with the help of an AI tool called Synthetic Chemist. Then the scientist used an AI programme called ‘Search Algorithm for Ligands (SAM)’. Which of the billions and trillions of algorithms would identify the one that would help make the best vaccine? AI has reduced the years of process required to develop a vaccine. Unsupervised learning, supervised learning and reinforcement learning of AI are used for tasks ranging from studying a virus to producing a vaccine.

Some time ago, Sujan Chapagai’s ‘Phool’ song was heard in the voice of Narayan Gopal. How did the late singer Narayan Gopal sing this song? This is also a part of AI, which is the best of generative AI. Such a generative AI tool can change your voice to the voice of a famous singer or celebrity by identifying the style of singing, voice pitch, etc.

Generative AI takes data in the form of text, photo, video design, audio note or any other input and creates an exact replica with the help of different AI algorithms. This includes photos, audio, voice, essays, problem solving, and deep fake content. Chat GPT, Bard AI, Avatar AI, and Microsoft Bing’s Image Creator are some famous examples of Generative AI. As a modern part of AI, generative AI is a very complex subject.

As AI becomes a self-learner, it becomes increasingly difficult for a computer scientist to understand it and know how a self-taught algorithm reaches conclusions. As its capacity increases, its use in our daily life also increases.

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