Learning from examples
A neural network is a computational model whose parameters are adjusted using examples. Training helps it identify patterns between words, features in pictures or properties of sound. It then applies those patterns to new inputs.
Different tools, different tasks
Text models can draft a letter, explain a topic or suggest code. Image models create pictures from descriptions. Audio tools transcribe or synthesize speech; music models create compositions. Exact capabilities depend on the tool.
Where to begin
Choose a small task with a clear outcome: an advert draft, lesson outline, headline options or visual idea. Supply source facts, audience and format. Tasks with easy-to-check results make the benefit easier to judge.
Models make mistakes
Fluent output is not a guarantee of accuracy. Check numbers, names, links and important claims against original sources. Avoid unnecessary personal or confidential data. You decide whether a result is suitable to use.
Your first prompt
Try: “Outline a short presentation of my project for new customers. Use only the facts below. Give five slides with one heading and one point each. Ask questions first if information is missing.” Then refine one part at a time.