AI explainers
AI Explainers in Plain English
AI announcements often assume you already know the vocabulary. This hub explains the background ideas in normal language so news about models, agents, benchmarks, training data, and AI tools is easier to follow.
Use this page when a news brief mentions a term that sounds technical but affects everyday choices at work, school, or home.
Suggested beginner path
- Start with the AI Glossary for short definitions.
- Read AI Models to understand model releases and assistant updates.
- Use AI Questions Answered for common beginner questions.
- Check AI Safety and Privacy before using AI with sensitive information.
Plain-English explainer topics
Large language models
What people mean when they say LLM, model, context window, prompt, benchmark, inference, or fine-tuning.
AI agents
How agent tools differ from ordinary chatbots, and why human review still matters.
RAG and retrieval
Why some AI systems look up documents before answering and why that does not automatically make every answer correct.
Explainer-style articles
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AI Model Training vs Inference: The Simple Difference
Training is how an AI model learns patterns before use. Inference is the moment the trained model uses those patterns to answer a new…
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What Is RAG? Retrieval-Augmented Generation in Plain English
RAG is a way to connect an AI answer to selected documents, databases, or search results before the model writes its response.
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What Is an AI Agent? A Plain-English Guide
An AI agent is software that can use AI to pursue a goal, plan steps, use tools, observe results, and keep going within set…
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Google Wants Every U.S. Teacher to Get AI Training
Google says it will make free Gemini and NotebookLM training available to 6 million U.S. educators through ISTE+ASCD.
Relevant recent news
For current developments, use Latest AI News. For practical business use, use AI for Small Business.
Evergreen explainers
New evergreen AI explainers
- What Is an AI Agent?: Understand tool-using systems before following agent news.
- What Is RAG?: See how AI systems retrieve approved information before answering.
- AI Model Training vs Inference: Separate model-building news from answer-time use.
Side-by-side comparison
Training Vs Inference
Training is how a model learns patterns. Inference is when it uses those patterns to answer a new prompt.
Comparison explaining that training learns patterns before use while inference uses learned patterns when a user asks something.
| Question | Training | Inference |
|---|---|---|
| Basic idea | Training: model learns patterns from data. | Inference: model uses learned patterns to answer a new prompt. |
| When it happens | Training is usually expensive and done before use. | Inference happens when the user asks something. |
| Practical caveat | Fine-tuning can update a model for a narrower task. | The answer still needs checking when accuracy matters. |