How to Spot AI Hype
To spot AI hype, look for real deployment details, clear limits, source-backed claims, relevant benchmarks, and evidence beyond a polished demo.
How to Spot AI Hype Read More »
Plain-English AI explainers that break down confusing terms, model updates, and industry claims.
To spot AI hype, look for real deployment details, clear limits, source-backed claims, relevant benchmarks, and evidence beyond a polished demo.
How to Spot AI Hype Read More »
Multimodal AI means an AI system can work with multiple kinds of information, such as text, images, audio, video, code, or documents.
Multimodal AI Explained: Text, Images, Audio, and Video Read More »
An LLM is an AI model trained on large amounts of language so it can predict and generate text for tasks such as drafting, summarizing, and answering questions.
What Is an LLM? Large Language Models Explained Simply Read More »
Synthetic data is artificial data created to resemble some patterns of real data, often for testing, analysis, privacy research, or AI development.
What Is Synthetic Data in AI? Read More »
Training is how an AI model learns patterns before use. Inference is the moment the trained model uses those patterns to answer a new request.
AI Model Training vs Inference: The Simple Difference Read More »
RAG is a way to connect an AI answer to selected documents, databases, or search results before the model writes its response.
What Is RAG? Retrieval-Augmented Generation in Plain English Read More »
An AI agent is software that can use AI to pursue a goal, plan steps, use tools, observe results, and keep going within set limits.
What Is an AI Agent? A Plain-English Guide Read More »
Google says it will make free Gemini and NotebookLM training available to 6 million U.S. educators through ISTE+ASCD.
Google Wants Every U.S. Teacher to Get AI Training Read More »