AI in a Nutshell: Everything You Need to Know in 2024

Lately, everyone seems to be going crazy over artificial intelligence. Thanks to widely available apps like Midjourney and ChatGPT, the internet is flooded with a wave of information and guides about this innovative technology.

If you’re wondering what all the fuss is about and what exactly artificial intelligence is, you’ve come to the right place. In this short article, we’ll strive to explain all the key concepts related to AI comprehensively.

We invite you to read on!

What is Artificial Intelligence?

Before we explain the concept of artificial intelligence, it’s worth noting that its definition has significantly evolved over time. In the past, even early European computers were considered by engineers to be “logical machines” or “mechanical brains” because they were able to replicate arithmetic and memory. As technology has advanced, the concept of AI has changed. So, what does it mean today?

Artificial Intelligence (AI) is a field that combines computer systems and datasets to simulate human intelligence. It involves mimicking tasks previously performed by humans and performing complex tasks more human-like than ever before. Artificial intelligence is based on modeling human thinking and cognitive processes. It can help solve problems, make decisions, and perform tasks that require speed, accuracy, and complex thinking. It includes, among other things, planning, problem-solving, language understanding, voice and image recognition, learning, and any other task considered “intelligent.”

7 examples of using artificial intelligence in everyday life

Let’s take a look at some specific examples to better understand artificial intelligence. Nowadays, almost everyone with internet access uses AI-based solutions, although they often don’t even realize it. Below are seven popular examples of AI being used in everyday life:

  1. Voice assistants – programs like Siri, Alexa, or Google Assistant use AI to recognize speech and provide answers to questions asked by users.
  2. Filters in social media – apps like Instagram or Snapchat use AI algorithms to recognize faces and automatically apply real-time effects.
  3. Shopping recommendationsmany online stores, such as Amazon or Aliexpress, use AI algorithms to analyze customer behavior and offer personalized offers.
  4. Personalized travel recommendations – travel companies and websites use AI algorithms to analyze user preferences and, based on that, offer them travel packages that best match their interests and needs.
  5. Product and content recommendations – services like Netflix, YouTube, or Spotify use AI-based recommendation systems to offer users content tailored to their preferences based on their previous activity.
  6. Translators – automatic language translation systems such as Google Translate or DeepL use Natural Language Processing (NLP), a subset of AI, to translate text in real time.
  7. Chatbots – computer programs that automatically answer user questions and help solve problems, for example, in online banking or e-commerce, are another popular solution based on NLP.
  8. Intelligent search engines – some tools for searching information on the web or specific websites also use AI technologies, such as natural language processing and machine learning. Thanks to this, they can better understand and interpret user queries to provide them with more relevant and personalized results.

6 key benefits of using artificial intelligence

AI is a rapidly developing technology. According to Grand View Research the value of the artificial intelligence market was $136.55 billion in 2022. Moreover, the same source predicts that within the next 8 years, it will reach a value of $1,811.8 billion, representing a compound annual growth rate (CAGR) of 37.3%.

What is driving this tremendous interest in this technology? Below are some key benefits of using artificial intelligence:

  1. Improving business efficiency: According to Accenture, AI can increase business productivity by up to 40%. By automating time-consuming and repetitive tasks such as invoice generation, data processing, or customer service, companies can dedicate this saved time to other activities that lead to faster company growth.
  2. Increasing customer satisfaction: AI enables the creation of more personalized and tailored products and services. An example is Spotify, which uses AI to recommend music tailored to the listener’s taste.
  3. Improving customer service: In today’s world, customers expect immediate answers to questions and customer service available 24/7. To meet these requirements, more and more companies use AI-based chatbots. These intelligent computer programs can work continuously, providing customers with answers to frequently asked questions and even performing simple tasks such as sending invoices or booking accommodation.
  4. Better data analysis: AI enables faster and more accurate analysis of large amounts of data, enabling a better understanding of the market and customers and making more accurate, data-driven business decisions.
  5. Increasing security: AI can help detect and prevent fraud and other irregularities. An example is PayPal, which has used AI for years to detect suspicious transactions and fraud.
  6. Improving medical processes: AI has many medical applications, such as therapy planning, improving clinical trials, or analyzing medical images. It can also help in the early diagnosis of many diseases, such as cancer.

An AI glossary for beginners

In publications related to artificial intelligence, you will also find a range of other terms related to this subject. To help you better navigate this terminology, we have prepared a small glossary of the most important terms related to AI.


  1. Machine learning – a field of artificial intelligence that enables computers to acquire knowledge through data, observations, and interactions with the world. The main goal of machine learning is to teach machines to recognize patterns in large data sets, which allows for adequate actions to be taken based on them.
  2. Neural networks – a subset of machine learning that mimics the human brain. Networks consist of interconnected artificial neurons that process information and pass it on. Like the human brain, information is processed in parallel by many interconnected elements, allowing for effective solutions to various problems.
  3. Deep learning – a subgroup of machine learning that uses neural networks with a more complex architecture than standard machine learning algorithms. The main advantage of deep learning is that neural networks can learn data representations, which means they can extract features and patterns from data themselves without humans needing manual feature definition. This technology has many applications for precisely analyzing large and complex data sets.
  4. Data science – an interdisciplinary field that deals with the study, analysis, and interpretation of data. Data science uses various methods and tools, including machine learning, to extract valuable information from large data sets.
  5. Big data – collecting and analyzing huge data sets that are too large and complex to be easily processed by traditional methods and tools. Big data analysis allows for discovering hidden patterns, relationships, and dependencies between data, which can lead to valuable insights and business decisions.
  6. Computer vision – a field of artificial intelligence that enables computers to recognize and interpret images and videos. Computer vision technology is used in many applications, including face recognition, identification of road signs, and analysis of medical images.
  7. Natural language processing– a field of artificial intelligence that enables computers to analyze, interpret, and generate natural language. Natural language processing technologies are used, among others, in online translators, chatbots, and intelligent search engines.
  8. Generative AI – a type of artificial intelligence that allows for generating new content, such as text, images, or music. Generative AI uses machine learning, deep learning, and natural language processing.
  9. ChatGPT – an example of a generative AI system used to generate responses to questions asked of it. The program can learn based on the data entered into it, allowing it to achieve greater accuracy and precision in its responses over time.
  10. Midjourney – an interactive program-bot from the field of generative AI used to create images based on text. Its operation involves the user describing what they want to see, and then the program finds images that fit the description and combines them to create a unique composition.

We hope this article has given you a better understanding of these complex AI issues. Our team has extensive experience in this topic and will happily share their knowledge. Let us know if you have any questions or need clarification on other concepts!

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