Robots Atlas>ROBOTS ATLAS
react-czym-jest-paradygmat-rozumuj-i-dziaaj-w-agentach-llm-cover
Agentic AIParadigm

ReAct — what is the "reason and act" paradigm for LLM agents?

ReAct is an architectural pattern for large language models in which the model alternates between generating thoughts (reasoning), calling external tools, and reading observations back into its context. Understanding ReAct is a prerequisite for building any modern AI agent, because the Thought–Action–Observation loop sits underneath most agentic systems shipped today.

prompt-caching-czym-jest-i-jak-dziaa-logo
ComponentsAI Engineering

Prompt Caching — What It Is and How It Works

Prompt Caching is an optimisation mechanism in large language model APIs that allows repeated reuse of processed prompt fragments without recomputing them from scratch. For queries containing long, repetitive contexts — such as extensive system instructions, documents, or few-shot examples — it can make API calls up to ten times cheaper and several times faster.

claude-opus-48-model-anthropic-z-mechanizmem-adaptive-thinking-logo
AI / MLSoftware

Claude Opus 4.8 — Anthropic's Flagship Model with Adaptive Thinking

Released on May 28, 2026, Claude Opus 4.8 is the current leader in comprehensive AI intelligence rankings. With its Adaptive Thinking mechanism, one-million-token context window, and revolutionary agentic capabilities, the model redefines standards for autonomous coding, data analysis, and enterprise business tasks.

AnthropicConstitutional AI
Multi-Agent Systems Cover
Agentic AIArchitecture

Multi-Agent Systems: How AI Learns to Cooperate and Compete

Artificial intelligence has stopped working alone. Multi-Agent Systems (MAS) create networks of specialized agents that negotiate, compete, and cooperate — reshaping the AI paradigm from the ground up.

Tokeny Cover
AI ArchitectureArchitecture

The Transformer Architecture: How Attention Rewrote the Rules of AI

The Transformer is a neural network architecture that in 2017 replaced recurrent models and launched the era of large language models. Understanding how it works is the key to grasping where ChatGPT, BERT, GPT-4, and Vision Transformers came from.

Transformer
Embeddings in AI: How Machines Understand the Meaning of Words
AI ArchitectureTechnology

Embeddings in AI: How Machines Understand the Meaning of Words

Embeddings are mathematical representations of words, sentences, and documents in a multidimensional vector space — the foundation of modern NLP, semantic search, and RAG architectures. Discover how Word2Vec, GloVe, BERT and cosine similarity became the common language of machines.

Agent AI — czym jest, jak działa i gdzie jest stosowany Cover
Agentic AISoftware

AI Agents — What They Are, How They Work, and Where They're Used

An AI agent (also called agentic AI) is a category of systems capable of autonomously planning and executing multi-step tasks without continuous human supervision. It is not a chatbot — it is a technology layer that turns language models into independently operating digital collaborators.

llm-co-to-jest-i-jak-dziaa-duzy-model-jezykowy-cover
AI / MLArchitecture

LLM — what it is and how a large language model works

Large language models (LLMs) are a class of artificial intelligence systems built on neural networks and trained on massive text corpora to generate and understand natural language. Understanding their architecture and limitations is essential for anyone using AI tools or making decisions about depl

TransformerTokenizationEmbeddingsSelf-Attention+22
physical-ai-czym-jest-i-jak-dziaa-fizyczna-sztuczna-inteligencja-logo
Autonomous SystemsParadigm

Physical AI — what it is and how it works

Physical AI is the branch of artificial intelligence development that moves AI capabilities from purely digital environments into the physical world — enabling machines to perceive their surroundings, reason about them, and act in real time. Understanding this paradigm is essential for anyone following where robotics, industrial automation, and autonomous systems are heading in the coming decade.