AI Training Series: What is It, What Does It Do?

Artificial intelligence (AI), machine learning (ML), deep learning (DL) and vector databases (Vector DB) have become one of the most popular topics in the software world in recent years. But most people are still confusing these terms or don’t know exactly how they work.

In this series, we will discuss these concepts in detail, starting from scratch. We will explain what they work for, how they work and with what tools they are used.

🚀 Our first stop: Artificial Intelligence (AI)!

1️️ What is Artificial Intelligence (AI), What Is It Useful for?

📌 What is Artificial Intelligence?

Artificial Intelligence (AI) is the technology that enables computer systems to think, make decisions and learn like humans. AI can make predictions and provide automation by extracting patterns from large data sets.

🔹 What Is the Use of Artificial Intelligence?
* Voice Assistants → Siri, Alexa, Google Assistant
* Visual Recognition → Face recognition, license plate reading
* Recommendation Systems → Netflix, YouTube, Spotify algorithms
* Chatbots → ChatGPT, customer service bots

🛠️ With What Tools Is It Made?
* Python → The most common programming language for AI
* TensorFlow & PyTorch → For deep learning models
* OpenAI API & GPT-4 → For language model applications
• IBM Watson → For Enterprise AI solutions

🚀 AI is integrating into every aspect of our life! But there is a step beyond this: Machine Learning (ML).

2️️ What is Machine Learning (ML), What Does It Do?

📌 What is Machine Learning?

Machine Learning (ML) is a sub-branch of artificial intelligence. It allows creating algorithms that can make predictions by learning from data. For example, it is thanks to ML that Netflix recommends suitable movies for you, or Gmail detects spam emails.

🔹 What Is the Use of Machine Learning?
* Spam Filters → Gmail, Outlook spam detection
* Financial Forecasts → Stock market and credit scoring
* Autonomous Vehicles → Tesla’s driverless systems
• Medical Diagnostics → AI systems that diagnose diseases

🛠️ With What Tools Is It Made?
* Scikit-learn → For classical ML algorithms
* XGBoost & LightGBM → Advanced ML models
* Pandas & NumPy → Data analysis and processing
• To deploy Google Cloud AI & AWS SageMaker → ML models

🚀 ML is an excellent tool for learning from large data sets. But for more complex problems, we need Deep Learning (DL)!

3️️ What is Deep Learning (DL), What Does It Do?

📌 What is Deep Learning?

Deep Learning (DL) works by using artificial neural networks that mimic neural networks in the brain. It is more powerful than ML for analyzing and learning complex data.

🔹 What Is the Use of Deep Learning?
* Autonomous Vehicles → Tesla, Waymo
* Voice Recognition → Google Translate, Siri
* Deepfake Technology → Fake video and audio production
• Medical Imaging → MRI and X-ray analysis

🛠️ With What Tools Is It Made?
* TensorFlow & Keras → For deep learning models
* PyTorch → For academic research and DL projects
* OpenCV → Image processing and face recognition
* Hugging Face Transformers → Advanced language models

🚀 DL works with very large data sets, so classic databases will not be enough. That’s why Vector Databases (Vector DB) come into play!

4️️ What is a Vector Database (Vector DB), What is It Useful for?

📌 What is a Vector Database?

Vector Databases are databases specially developed for AI and ML. Unlike traditional SQL or NoSQL systems, they focus Decently on similarity-based search.

🔹 What is a Vector Database Useful For?
* Image Search → Google Lens Decode Pinterest image searches
* Natural Language Processing (NLP) → ChatGPT, text analysis
* Recommendation Engines → Amazon, Spotify, Netflix
* Anomaly Detection → Financial fraud and security systems

🛠️ With What Tools Is It Made?
* FAISS (Facebook AI Similarity Search) → For large-scale vector searches
* Pinecone Dec → AI-supported search systems
• Weaviate → Open source vector database
* Milvus → Real-time big data processing

🚀 Vector databases are a critical component for AI and ML projects and will be used much more in the future!

Result

In this article, we have examined the concepts of AI, ML, DL and Vector DB in detail:
✅ AI → General artificial intelligence applications
✅ ML → Learning from data and making predictions
✅ DL → Deep learning with artificial neural networks
✅ Vector DB → Optimized data storage for AI and ML

⏭️ Next Post: The Logic of AI Operation and Its Uses

Keep following this series! If you have any questions, don’t forget to comment. 🚀🔥