LLM Fundamentals: Do Token ao Sistema em Produção

📰 Medium · LLM

Learn the fundamentals of Large Language Models, from tokenization to system production, and understand how they work in a real-world architecture

intermediate Published 12 Apr 2026
Action Steps
  1. Understand the concept of Large Language Models and their role in AI generative technology
  2. Learn about tokenization and how it works in LLMs
  3. Study the message roles protocol and its importance in LLM interactions
  4. Explore how embeddings work in LLMs and their significance in natural language processing
  5. Investigate how the Spring AI organizes LLMs in a real-world architecture
Who Needs to Know This

This article is beneficial for AI engineers, data scientists, and software engineers working with LLMs, as it provides a comprehensive guide to understanding the technology and its applications

Key Insight

💡 LLMs are trained to predict the next token in a sequence, and understanding tokenization, message roles, and embeddings is crucial for working with them

Share This
Discover the fundamentals of Large Language Models and how they work in a real-world architecture #LLMs #AI #NLP
Read full article → ← Back to Reads