Artificial Intelligence (AI) is a field of computer science focused on creating intelligent machines. These machines can perform tasks that normally require human thinking, such as learning, problem solving, and decision making.
Imagine having a robot that can not only vacuum, but also learn from its mistakes, understand your voice commands, and even hold a simple conversation with you. This is exactly what artificial intelligence does.
How does Artificial Intelligence work?
Modern AI systems, such as those powering chatbots or generating images from text, are primarily based on machine learning, more specifically deep learning and the transformer architecture. Sounds complicated? Don’t worry, I’ll explain!
Imagine teaching a dog the “sit” command. You show it many times what to do, give it treats when it does it right. Eventually, the dog learns to associate the word “sit” with the correct action. Machine learning works similarly, but instead of a dog, we have a computer, and instead of treats, we have data.
- Data and Tokens: The computer receives a large amount of data, for example text. This data is divided into small pieces called tokens (e.g. words).
- Magic Vectors (Embeddings): Each token is converted into a sequence of numbers, i.e. a vector. It’s like a secret language that the computer understands. It’s important that words with similar meanings have similar vectors.
- Transformer Architecture: This is where all the magic happens. The transformer is a special type of neural network that can analyze these vectors and learn relationships between words.
- Attention Mechanism: It’s like a superpower of the transformer. It allows focusing on the most important words in a sentence and understanding their context. For example, in the sentence “The cat sat on the mat”, the attention mechanism will help the model understand that “sat” refers to “cat” and “mat”.
- Neural Network: After being processed by the attention mechanism, the data passes through several layers of the neural network, learning increasingly complex relationships.
- Learning: The entire learning process consists of the model receiving lots of data and trying to predict what the correct output should be (e.g. the next word in a sentence). If it makes a mistake, it adjusts its internal settings to be closer to the correct answer next time. It’s like a trial-and-error method, but on a large scale!
- Generation: After completing training, the model is ready to work. It can generate new texts, answer questions, and even create images based on what it has learned.
Types of Artificial Intelligence:
- Weak AI (Narrow AI): This is a type of AI that can only perform specific tasks. For example, a chess program is weak AI because it only knows how to play chess but cannot, for example, drive a car. Most AI systems we know today are weak AI.
- Strong AI (General AI/AGI): This is a type of AI that would be as intelligent as a human. It could learn, solve problems, and make decisions in any field, not just a specific one. For now, strong AI is something for the future, but scientists are working hard on it.
Why do we need Artificial Intelligence?
AI has many advantages and can be used in various fields:
- Automation: AI can take over boring and repetitive tasks, leaving humans more time for creative activities.
- Better Efficiency: In many fields, such as medicine or finance, AI can help make better and faster decisions.
- New Possibilities: AI enables creating things that were previously impossible, such as generating realistic images from text descriptions.
Should we fear Artificial Intelligence?
Like any technology, AI also has its dark side:
- Job Loss: Some professions could be replaced by machines.
- Privacy: AI systems can collect and process large amounts of data about us, which can raise concerns about our privacy.
- Autonomous Weapons: There is a risk that AI could be used to create weapons that can kill without human control.
Let’s hope that, like other advanced technological devices - the hammer - most people will use it as intended :)
The Future of Artificial Intelligence
Artificial intelligence is a field that is developing very rapidly. It’s hard to predict what the future will bring, but AI will undoubtedly play an increasingly important role in our lives. It’s important that we are aware of both the benefits and risks associated with this technology and that we develop it wisely.
Popular AI Models:
Here are some examples of well-known AI models:
- GPT-4o: The latest model from OpenAI, which can process text, images, sound and video. It excels at text generation, language translation and maintaining conversations.
- Gemini 1.5 Pro: An advanced model from Google that can analyze large amounts of data, including text, images and sound. experimental version is Gemini Experimental 1206
- Gemini 1.5 Flash: A faster and more economical version of the Gemini model, ideal for simpler tasks. experimental version is Gemini 2.0 Flash Thinking Experimental
- DeepSeek-V3: A very efficient language model that can process very long texts. Great for assisting with code writing.
- ImageFX: A Google tool that allows easy creation of images from text descriptions.
- Stable Diffusion 3: An open-source model for generating very realistic images from text.
- Midjourney (v6): A popular tool for creating images, known for its artistic style. Available as a bot on Discord.
Summary
Artificial intelligence is a fascinating and rapidly developing field. While it may raise some concerns, it has great potential to improve our lives and help us solve difficult problems. Even if you’re completely new to this topic, it’s worth getting interested and learning about it, because it will undoubtedly play an increasingly important role in the future.
