Category
Fundamentos
AI news and tutorials in the “Fundamentos” category.
How to look for bias in AI answers and content
Look for bias in AI answers with comparable cases: inspect assumptions, omissions and language, record differences and review without promising neutrality.
How to investigate missing values before AI data analysis
Investigate missing values before AI analysis: distinguish zero from empty fields, check collection and document treatment without inventing information.
How to create a data dictionary with AI assistance
Create a data dictionary with AI: define columns, units, accepted values and missing-data rules, then verify examples and questions with the source owner.
Chatbot or search engine: how to choose for each question
Learn when to use a chatbot, search engine or both. Separate explanation, current information and verification before relying on an AI answer.
How to choose an AI tool for your task
Choose an AI tool based on your task, permitted data and result criteria. Run a small practical test before subscribing or changing your workflow.
AI agents: how to define goals, tools and limits
Define an AI agent task through a verifiable goal, necessary tools, execution limits and a clear condition for stopping the work and reporting its result.
Keyword or semantic search: how to choose
Compare keyword, semantic and hybrid search using real questions, codes and versions. Learn to test results before choosing a retrieval strategy.
What embeddings are and how they help find information
Understand embeddings without advanced math: numerical representations, similarity search and how to test whether retrieved documents are useful.
What to review before sending personal data to AI
Review material before sending it to AI: necessity, permission, identifying details, tool policies and alternatives using fictional examples or reduced data.
How to study a new subject with AI without copying answers
Use AI for study questions, examples and exercises. Build a sequence that asks you to explain concepts and check references instead of only reading answers.
AI hallucinations: how to spot and reduce invented answers
Learn signs of AI hallucinations and a workflow for checking claims, allowing uncertainty and separating supplied facts from information needing verification.
What is an LLM? A simple explanation (no math)
What is an LLM? Understand in 8 minutes, no math, how a Large Language Model works, why it "hallucinates", and how to use generative AI safely.
What are tokens and how do they work? (a simple guide)
What are tokens in AI? Understand in 6 minutes, no math, what they are, how text becomes tokens, and how the model reads and generates each one.