Introduction
Getting started with AI Summary Hub and an overview of AI fields.
Welcome to AI Summary Hub — your single source of truth for modern AI concepts.
This hub is built for deep knowledge: each topic gives you clear definitions, how it works (with diagrams and code where useful), and links to official documentation and codelabs so you can go from understanding to building.
What you'll find here
This wiki covers 150+ in-depth articles across 50+ categories, available in EN and pt-BR, including:
- Fundamentals — Machine learning, deep learning, neural networks
- Transformers & LLMs — Architecture, BERT, GPT, fine-tuning, prompt engineering, streaming
- RAG — Retrieval-augmented generation, vector databases, embeddings
- Agents & subagents — AI agents, multi-agent systems, hierarchies
- Reasoning patterns — Chain-of-thought, tree-of-thoughts, ReAct, RDD (retrieval-decision-design)
- Spec-driven development — Building AI systems from specifications
- Fields — NLP, computer vision, speech, robotics, multimodal AI
- Safety, ethics, evaluation — AI safety, bias, explainability, benchmarks
- Infrastructure & deployment — Local inference, edge reasoning, model compression, quantization
- Tools — Hugging Face, LangChain, Cursor, Claude Code, Antigravity, Kiro, PyTorch, TensorFlow
- Case studies — ChatGPT, DALL·E, Claude, Gemini, BART, Grok, DeepSeek, Qwen
Each topic includes definitions, examples (code and diagrams), pros/cons, benchmarks, and practical resources linking to official docs, codelabs, and papers.
When to use this hub
| Goal | Where to start |
|---|---|
| New to AI | Fundamentals then Neural Networks |
| Building with LLMs | LLMs, RAG, and Agents |
| Exploring reasoning | Reasoning Patterns and RDD |
| Running models locally or at the edge | Local inference and Edge reasoning |
| Multimodal (text + image, etc.) | Multimodal AI |
| Deploying models in production | MLOps and Infrastructure |
Getting started
- New to AI? Start with Fundamentals and Neural Networks.
- Building with LLMs? See LLMs, RAG, and Agents.
- Exploring reasoning? Check Reasoning Patterns and RDD.
- Running models locally or at the edge? See Local inference and Edge reasoning.
- Multimodal (text + image, etc.)? See Multimodal AI.
Use the sidebar to browse all topics or the search bar to find specific concepts.
Practical resources
- Google AI for Developers — Gemini, APIs, and guides for building AI applications
- Hugging Face NLP Course — Practical course from transformers to production LLMs
- From Prototypes to Agents with ADK (Codelab) — Build your first agent with Google's Agent Development Kit
- fast.ai – Practical Deep Learning — Top-down, code-first deep learning course for practitioners