LoRA (Low-Rank Adaptation)

LoRA (Low-Rank Adaptation) is an efficient method for adapting large AI models to specific tasks without having to retrain the entire model. LoRA can be thought of as a small, specialized add-on that is applied to the original AI model. This approach is comparable to an expert acquiring additional specialized knowledge without altering their foundational … Read more

Reasoning

Reasoning, in the context of artificial intelligence, describes a system’s ability to draw logical conclusions, recognize connections, and derive new insights based on existing information. In AI systems like ChatGPT, reasoning means that they don’t just reproduce memorized answers but can reach independent conclusions by connecting different pieces of information. A simple example: if the … Read more

Overfitting

Overfitting is a common problem in AI training where the model learns the training data too precisely, rather than understanding general patterns. It can be compared to a student who memorizes example problems from a textbook instead of understanding the underlying mathematical principles. When faced with slightly different problems in an actual test, they fail. … Read more

Few-Shot Learning

Few-Shot Learning refers to a method in artificial intelligence where an AI model can learn new tasks from just a few examples. Unlike traditional machine learning, which often requires thousands of training samples, Few-Shot Learning can work with just a handful of examples – sometimes as few as two or three. It can be compared … Read more

Transformer

Transformers are a groundbreaking architecture for artificial neural networks, developed by Google in 2017, and now form the foundation for modern AI language models such as ChatGPT, Claude, or Google’s own Gemini. The name “Transformer” refers to these systems’ ability to transform input data (for example, texts) into another form. What makes Transformers special is … Read more

LLM Router

An LLM Router (Large Language Model Router) is a system that automatically directs incoming queries to the most appropriate language model. Similar to a traffic control system, the router determines which of the available AI models can solve a specific task most efficiently. This selection is based on various criteria such as the type of … Read more

Foundation Model

Foundation Model refers to a large AI model trained on vast amounts of data that serves as a foundation for various specialized applications. It can be thought of as a base upon which other AI applications are built. These models are initially trained on a broad spectrum of data – from texts and images to … Read more

Large Language Model

A Large Language Model, commonly abbreviated as LLM, is an advanced artificial neural network designed to understand, generate, and process human language. These models are termed “large” because they are trained on vast amounts of textual data and can contain billions of parameters. LLMs are capable of performing a wide range of tasks, including text … Read more

Mixture of Experts

Mixture of Experts (MoE) is a concept in artificial intelligence that can best be understood as a team of specialists. In this approach, a complex task is divided among multiple smaller, specialized models – the so-called “experts” – instead of using a single large model for everything. A central “gatekeeper” or “router” decides which expert … Read more

Chain of Thought

Chain of Thought is a concept in artificial intelligence that describes the ability of AI systems to solve complex problems step-by-step, much like humans do. This method allows AI models to explain their thought processes in a way that humans can understand. Instead of just providing a final answer, the AI shows the individual steps … Read more