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Artificial intelligence and neural networks for beginners: A complete guide to start using AI today

This guide will help you understand the basics and start using AI within 10 minutes, even if you’ve never done it before. We will explain everything in simple terms, avoiding complex jargon: covering key concepts, introducing popular platforms, and addressing important points regarding security and copyright.

Do you think artificial intelligence (AI) is only for programmers and futurists? Not anymore. Today, most modern devices and applications use AI technology — from smart assistants that help write texts and create images to intelligent video surveillance systems like our Xeoma application, capable of recognizing faces and suspicious behavior in real time. AI is becoming an integral part of many fields, making our lives easier, safer, and more comfortable. Now, you too can get to know AI up close.

Contents:

AI development

1. What is AI and beyond : Key concepts in 5 minutes

Let’s clarify the basic terms right away so you understand what we’re talking about.

Artificial intelligence
Machine learning
Neural network
Deep learning
Generative AI
Large language model
Prompt
AI hallucination

Artificial intelligence (AI) is an umbrella term for technologies that enable machines to mimic human intelligence: solving problems, learning, recognizing speech and images, analyzing vast amounts of data, predicting events, etc. Simply put, the goal is to create an intelligent machine.

Machine learning (ML) is not the only, but the primary way to “teach” a computer. Instead of writing strict rules for it (e.g., “if the word is ‘coffee,’ categorize it as ‘beverages'”), we provide it with many examples, and it finds patterns on its own. It’s like teaching a child to recognize a cat: you don’t explain the theory; you just say “this is a cat” many times.

Neural network is a specific and very popular machine learning architecture inspired by the human brain. It consists of “neurons” — layers of algorithms that transmit and process information. The more “layers” a neural network has, the more powerful it is and the better it handles complex tasks. Neural networks are behind all modern breakthroughs in AI.

Deep learning is an approach to machine learning that utilizes very complex and large neural networks with multiple layers. It is these “deep” networks that enable solving truly complex tasks: for example, recognizing objects in video with near-human accuracy, translating speech in real time, or making medical diagnoses based on scans.

Generative AI (GenAI) is the next step. While regular AI might only recognize a cat in the picture, generative AI can draw it from your description. It doesn’t analyze existing content but creates new content: text, images, music, code.

Large language model (LLM) is a type of neural network trained on enormous amounts of text (books, articles, website code). It learns to predict the next word in sequence. ChatGPT, Claude, and Jasper are interfaces for interacting with such models. They don’t “understand” meaning like a human does, but they generate incredibly plausible and coherent text.

Prompt is your query or instruction for the AI. It’s what you input in a chat to get the desired result. The quality of the response almost always depends on the quality of the prompt. The more precise and detailed your instructions, the better the output. A prompt is not just a question, it’s a command.

AI hallucination is a situation when a neural network confidently outputs completely false information. It may invent nonexistent facts, quotes, historical events, or scientific concepts. This happens because the model tries to generate the most plausible text patterns based on its training data rather than objective truth. It’s critically important to always verify facts, especially numbers, names, and dates.

A simple analogy: Imagine that AI is the entire kitchen. Machine learning is one way of cooking (e.g., baking). A neural network is your multifunctional convection oven. Deep learning is using all the oven’s advanced features (like “even heat from all sides,” “precise humidity control,” and “automatic bread-baking programs”) to create complex culinary masterpieces. And generative AI is the built-in “smart chef” in the oven that allows you to create a completely new dish simply by inputting a list of ingredients. Your prompt is the recipe you give the oven. If you write “make a pie” in the recipe, the result will be random. But if you specify “apple pie, 20 cm diameter, gluten-free, with cinnamon”, the result will match your expectations exactly. A hallucination is when then oven, unable to find a needed ingredient, confidently substitutes it with another one and serves you the dish as if it were correct. For example, it adds garlic instead of vanilla because those words appeared together in some data. It looks appetizing but is inedible. Always test your results!
 

A bit of history: How AI journeyed from dream to reality

The history of AI is not a rapid ascent but a path of trial and error, periods of fervent enthusiasm followed by “winters” of disappointment. Knowing this context helps explain why the breakthrough happened now.

  • 1950s: The birth of a dream. The era begins with British mathematician Alan Turing‘s fundamental question: “Can machines think?” His Turing Test was the first attempt to define machine intelligence. Scientists created the first programs mimicking intellectual tasks, like the Logic Theorist (1956), capable of proving logical theorems. The term “artificial intelligence” was coined in 1956 at the Dartmouth Conference, where scientists optimistically claimed they would create a machine capable of all human intellectual tasks in a few years. This was an era of high hopes and the first, albeit, simple programs able to play checkers or solve basic logic problems.
  • 1970s–80s: The “AI winters” and expert systems. It became clear that early promises were unachievable due to lack of computing power and data. The first “AI winter” brought funding cuts and reduced interest. During this period, expert systems — programs encoding specialists’ knowledge as “if-then” rules — emerged. They were successfully used for diagnosis in medicine or in manufacturing but were expensive, fragile, and unable to learn. By the late 1980s, the limitations of this approach caused disappointment again, leading to the second “AI winter.”
  • 1980s–90s: The quiet revolution of neural networks. Parallel to the decline of expert systems, a key event took place in research labs: the revival of neural networks. The idea, proposed back in the 1940s, received new life through the discovery of the backpropagation algorithm, which enabled effective training of multilayer networks. Pioneers like Geoffrey Hinton laid the mathematical foundations for future deep learning, although their work remained somewhat in the shadows due to a shortage of data and computing power at the time.
  • 2010s: Big data and deep learning. A turning point arrived when three key factors converged:
    1. Big data. The Internet had accumulated colossal volumes of information – texts, images, videos.
    2. Computing power. The advent of powerful Graphics Processing Units (GPUs), ideal for the parallel computations required for training neural networks.
    3. Algorithms. The development of deep learning methods — neural networks with many layers — allowed for the creation of much more complex and accurate models.

    In 2012, the neural network AlexNet decisively won the ImageNet competition, demonstrating deep learning’s superiority. This success sparked today’s AI revolution.

  • 2020s to present: The era of large language models and generative AI. The next step was scaling models. Large language models like OpenAI’s GPT were trained on vast text corpora and showed impressive capabilities in generation and language understanding. Models like Google’s BERT also became widely used for text analysis. The launch of ChatGPT in 2022 was a cultural shock, making AI massively accessible. Meanwhile, generative AI expanded beyond text to create images, audio, and video through tools like DALL·E, Stable Diffusion, and others. Today, AI is a practical tool available to everyone.

This journey from Turing’s philosophical questions to modern ChatGPT took over 70 years. And now, we are not at the end, but at the beginning of a new, incredibly exciting chapter in technology development.

 

2. How is AI used today?

AI today is integrated into many human activities, significantly changing traditional approaches and increasing efficiency. Key applications include:

  • Medicine. AI aids in diagnosing diseases with high accuracy by analyzing medical data and images, and creates personalized treatment plans considering patient specifics. For example, AI helps doctors detect cancers early, saving thousands of lives annually.
  • Finance. AI is used for automated trading, risk assessment, and fraud detection, improving the safety and profitability of operations.
  • Marketing. AI enables personalized ad campaigns by analyzing customer behavior and predicting preferences, boosting promotion effectiveness.
  • Education. Intelligent educational platforms adapt programs to individual learner levels and interests; interactive textbooks make learning more engaging.
  • Transportation. Technologies for autonomous vehicles are developing; these can navigate complex road situations independently and ensure safety.
  • Manufacturing. AI optimizes production processes, controls quality, and promotes automation, reducing costs and increasing productivity.
  • Entertainment. AI powers personalized recommendations for movies, music, and games, and helps create new content, making leisure more interesting and diverse.
  • Security and video surveillance. AI has revolutionized security systems by transforming cameras from simple recording devices into intelligent analytic centers. Modern systems like Xeoma use neural networks for facial recognition, detection of abandoned objects, visitor counting, and behavior analysis. This allows not just recording incidents but actively preventing them by automatically identifying suspicious activities (for example, loitering in restricted areas or perimeter breaches) and sending instant alerts to security teams.
Want to try intelligent video surveillance in action?
Download Xeoma for free!

Thus, artificial intelligence permeates many industries, helping solve complex problems and expanding capabilities for both business and daily life. This broad applicability makes AI one of the key technologies of our time.
 

AI-powered services

3. How can AI help you personally and in business?

Today, AI is available as convenient and practical services that help simplify work, save time, and improve the quality of results. Most of them offer free plans, allowing you to start using the technology without investments or technical knowledge. Below, we list some example services, but in reality, there are many more.

Working with text
Creating and editing images
Productivity and learning
Automation and video

Working with text

If you need help generating ideas, writing, or proofreading texts, AI will become your reliable assistant. You can ask AI to come up with interesting topics for posts, improve style, or adapt content for different platforms and audiences.

  • Generating ideas and drafts. Stuck in a creative rut? AI can help.
    Example prompt: “Come up with 10 post ideas for Reddit about a new fitness bracelet for women aged 25-35.”
    Services: ChatGPT, Jasper, Claude.
  • Proofreading and paraphrasing. Correcting mistakes, improving style, shortening texts.
    Example prompt: “Rephrase this text more formally and shorten it by 30%” [paste text].
    Services: QuillBot, Grammarly.
  • Creating social media posts. AI adapts one text for different platforms.
    Example prompt: “Write a short text for X and a longer post for FB based on this text” [insert text].
    Services: Notion AI, ChatGPT.

Creating and editing images

AI helps create unique illustrations based on your description — from realistic photos to creative images for blogs and presentations. Furthermore, it can edit photos by removing unwanted objects, adding details, and expanding the frame.

  • Generating images from descriptions. Create unique illustrations for blogs, presentations, or design references.
    Example prompt: “A realistic cat in a chef’s uniform cooking soup in a modern kitchen, photograph, high detail.”
    Services: Midjourney (quality leader, setup via Discord), DALL·E 3 (OpenAI’s model, accessible via ChatGPT), Stable Diffusion (for advanced users, can be installed on PC).
  • Photo editing. Removing unwanted objects, expanding images, adding backgrounds.
    Example: Remove a random passerby from the photo or “draw” a wall behind.
    Services: Adobe Photoshop (Generative Fill) (paid but very powerful), Luminar AI.

Productivity and learning

AI assistants significantly simplify searching for and structuring information, help create presentations, documents, and study plans, boosting your productivity and accelerating learning.

  • Research assistant. Instead of just providing links, AI can structure and summarize information.
    Example prompt: “Explain quantum entanglement as if I were 10 years old. Give an analogy.”
    Services: Perplexity AI (perfect for this), ChatGPT.
  • Presentation and document creation. AI can assist with planning, structuring, and even design.
    Example prompt: “Create a 10-slide presentation outline for investors about my eco-tourism startup.”
    Services: Gamma, Canva AI, Notion AI.

Automation and video

AI allows you to create videos from text with digital voiceovers nearly indistinguishable from human speech and automates creative processes, making them accessible even to non-professionals.

  • Creating video from text. Voiceover text with a digital narrator or even create videos with a digital avatar.
    Example: Create a promotional video for a product just by entering advertising text.
    Services: HeyGen, InVideo AI.
  • Voice generation and voiceover. Generating realistic speech for podcasts, videos, or audiobooks.
    Services: ElevenLabs (world leader in quality).

Using AI in these areas helps not only increase the quality and speed of work but also opens new possibilities for creativity and business growth. Starting today is very simple — just choose the right service and set a clear task.
 

4. Where to start learning AI? A step-by-step plan for beginners

Today, there are many AI-powered services, both universal and specialized. It’s easy for an unprepared person to get overwhelmed. What to do? Don’t try to take on everything at once. Start small. To avoid wasting time searching and quickly feel the benefits, it’s important to begin with one simple and clear task. This will help you get accustomed faster and stay motivated to move forward.

Step 1. Define one specific task. Ask yourself: “What routine or creative task takes up a lot of my time?” Not “I want AI,” but:

  • “I want to quickly write catchy article headlines.”
  • “I need to come up with an idea for a new product.”
  • “I need to edit this email to sound more confident.”

Step 2. Choose one tool. At the start, your best friend is ChatGPT or its analogues (Claude, Jasper). They are universal and simple. For images, start with DALL·E 3 — it’s accessible via browser and free within limits.

Step 3. Learn to craft prompts (requests). This is the most important skill! The quality of the answer depends 90% on the quality of your prompt. Experiment and be patient: mistakes and clarifications are a natural part of mastering AI.

  • Rule 1. Be specific and give context.
    Poor: “Write about coffee.”
    Better: “Write a short post for Reddit (no more than 500 characters) about launching a new line of espresso for home baristas. Target audience — men and women aged 25-40 who love coffee. Use emojis and a call to action ‘learn more in the carousel.’”
  • Rule 2. Assign a role. This is a magical trick.
    Example: “You are an experienced copywriter with 10 years in luxury automotive marketing. Write…”
    Example: “You are a strict physics teacher. Explain Ohm’s law to me in simple terms…”
  • Rule 3. Specify the format.
    Example: “Make a list…”, “write an email…”, “come up with 5 headlines…”, “provide the answer in a table…”

Step 4. Analyze and improve. AI rarely delivers a perfect result on the first try. It’s a dialogue.

  • If the text is too long: “Paraphrase it shorter.”
  • If the style is off: “Make the text more formal/friendly.”
  • You can point out a mistake: “You didn’t answer the question about delivery. Add that.”

 

Limitations of artificial intelligence

5. What not to forget: Ethics and limitations of AI

AI is a powerful tool, but it has serious limitations and important ethical nuances that must be considered.

Privacy. Before using any external service, be sure to review its data processing and storage policies. Many large companies offer reliable encryption and data protection mechanisms; however, full security also depends on your caution. Use strong passwords and two-factor authentication. Never upload confidential information to public AI services: client personal data, passwords, trade secrets, or unique know-how. Your queries might be used to train AI models.

Hallucinations and errors. AI can generate information that sounds very convincing but is completely fabricated. It does not “know” facts but predicts words. Always verify important facts, numbers, and quotes.

Copyright. The question of who owns AI-generated content — you, the model developer, or no one — is not fully resolved. It is important to carefully read the terms of service of the specific platform and comply with legal requirements. Use AI-generated content as a draft or idea, not as a final product, especially for commercial purposes.

AI content labeling. Many countries and platforms are introducing requirements to clearly indicate when text, images, or videos are created or processed by AI. This supports transparency and helps avoid misunderstandings or manipulations.

Algorithmic bias. AI is trained on real-world data which may contain stereotypes and errors. This can sometimes lead to discrimination or unfair results. It is important to critically assess AI outputs and not rely on them without verification.

Impact on the labor market. AI-driven automation is transforming many professions: some disappear, others emerge, and skill requirements change. This creates challenges for workers and society, demanding continuous learning and adaptation.

Responsibility for decisions. Despite AI’s assistant role, responsibility for important decisions—including in finance, medicine, and justice—lies with people and organizations, not machines.

AI is a tool, not a replacement for humans. It lacks critical thinking, true creativity, or empathy. Its role is to assist, enhancing your capabilities and taking over routine tasks so you can focus on what matters most. Ethics and mindfulness in AI use help maintain a balance between technology and human values.

This responsible approach to AI helps not only to avoid problems but also use its capabilities most effectively.
 

What does the future hold? A brief look at tomorrow

The future of artificial intelligence promises to be even more exciting and profound. New forms of AI are already on the horizon that will change the way we work and live daily.

AI agents. The next step is not just chatbots but true autonomous programs capable of performing complex multi-step tasks without constant supervision. Imagine AI booking your tickets to a game, finding flights and a hotel near the stadium, and then adding everything to your calendar.

Hyper-personalization. Educational platforms, entertainment services, and productivity tools will adapt so precisely to your habits, interests, and working style that using them will become incredibly convenient and effective.

Ubiquity of AI. Artificial intelligence will become an invisible but vital part of all digital products — from your refrigerator to your word processor. Like electricity, AI will surround us, making devices and services smarter and more useful.

Multimodality and integration. Modern AI models increasingly combine text, images, audio, and video into a single system, opening new possibilities for interaction and creativity.

Specialization. Rather than universal solutions, we will see more highly specialized AI systems for medicine, finance, law, and other fields that deliver more accurate and reliable results.

Local and offline models. AI capable of running directly on your devices without continuous Internet connection is developing — this will increase privacy and independence.

Ethics and regulation. As AI advances, attention to responsibility, transparency, and safety grows. These aspects will be key to public trust and the proper use of technology.

Economic impact. According to studies, by 2030 artificial intelligence could add up to $15.7 trillion to the global economy. This shift will lead to the creation of new business models, jobs, and industries as well as increase productivity and efficiency in many sectors.

According to Dario Amodei, Head of Research at Anthropic, within the next five years AI assistants will become personal consultants who understand the context of your life and work, helping you make crucial decisions and simplifying complex tasks. Thus, AI will continue to become a smarter, more personalized, and more seamless assistant, opening up new horizons of opportunity, convenience, and economic growth.
This vision of the future inspires us to start using AI today, not only to keep pace with technology but to be ready for a new level of interaction with the digital world.
 

Conclusion

Starting to use AI today is no more difficult than learning to use a smartphone 15 years ago. It represents a new level of digital literacy that opens incredible opportunities for creativity, increased productivity, and business growth. Artificial intelligence is your reliable assistant capable of taking over routine tasks and giving you a boost for new ideas.

However, it is important to remember data security, ethical standards, and verification of AI-generated results. Responsible use of technology will help maintain a balance between convenience and protecting personal information.

In the AI era, every step forward is a chance to work smarter, create more vividly, and live more comfortably. Take the first step today: open ChatGPT, Perplexity, or another service and try solving one real task. Only practice will quickly show how AI can become your indispensable assistant.

Welcome to the future, which begins right now!
 

FAQ: Frequently asked questions about AI

Here we have gathered answers to the most popular questions that beginners often have when first encountering artificial intelligence.

1. What free AI services are available?

Most modern AI services offer free plans with reasonable limits that are enough for getting started and handling many everyday tasks. Here are some reliable options:

  • For working with text: ChatGPT (free version 3.5), Claude (generous free usage limits), Jasper (free tier available).
  • For image creation: DALL·E 3 (integrated in free ChatGPT Plus/Microsoft Copilot versions), Midjourney Free Trial, Leonardo.AI (daily free generations).
  • For information search and analysis: Perplexity AI (answers questions citing sources).

These tools are more than enough to begin your journey in the world of AI without any financial investment.

2. What can you create with AI?

The list is almost endless! Here are just a few practical examples:

  • Texts: social media posts, blog ideas, letters, video scripts, poems, and even code.
  • Images: illustrations for articles, concept art, design references, unique greeting cards, and posters.
  • Multimedia: realistic voiceovers for text, creation of short videos from scripts, background music generation.
  • Business tools: presentation plans, market analysis, brand name or slogan ideas.
  • Personal assistants: workout plans, weekly menus, travel itineraries, summaries of complex articles.

Essentially, AI is a “creative muscle” that helps generate ideas and content in any field.

3. What types of AI solutions exist?

It depends on your tasks. They can be roughly divided into three types:

  • Universal assistants (chatbots), like ChatGPT or Google Bard. They help with a wide range of tasks, from writing texts to explaining complex concepts.
  • Specialized services. Solutions focused on one specific task. For example, Midjourney for generating images, ElevenLabs for voice creation, Gamma for creating presentations.
  • Built-in AI features in familiar programs. This is AI you are already using, possibly without noticing. For example, smart typing suggestions on smartphones (autocomplete), recommendations on YouTube and Netflix, or Zoom’s “Smart Background” feature.

4. What are some examples of AI in real life?

You encounter AI every day without even realizing it:

  • On your smartphone: voice assistants like Siri and Google Assistant, smart keyboard suggestions, facial recognition unlock.
  • On the Internet: personalized feeds on social platforms, product recommendations on Amazon and eBay, search engines Google and Bing.
  • In transportation: navigation apps like Waze that plan routes based on traffic, and driver assistance systems in modern cars.
  • In security: video surveillance systems in subways, offices, and smart homes that recognize faces and suspicious behavior.
  • In banking: systems that instantly detect fraudulent transactions on your card.

AI is no longer science fiction, but part of our everyday reality that makes life more convenient and safer.


October 22, 2025
 

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