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who ascribes meaning, based on their interpretation of the generated text. Thisunderstanding is key to leveraging the tool effectively and ethically.In the context of your project ideation and prototyping, ChatGPT can be apowerful ally, helping to generate ideas, draft project plans, and even simulatepotential dialogues or scenarios. Yet, to achieve the most beneficial results, youmust learn to navigate its usage effectively. This involves understanding theunderlying principles of how language models like ChatGPT operate, learningthe concept of tokens, and mastering the art of crafting effective prompts.This training module will guide you through these aspects, equipping you withthe necessary knowledge and skills to harness the full potential of ChatGPT foryour prototyping ideation phase.n 6. 1. 1. Understanding tokensIn language models like ChatGPT, a token is a basic unit of input forprocessing. This can range from a single character to an entire word, dependingon the language and the specific tokenisation process. For instance, in English,a token is typically a whole word (like %u201capple%u201d), while in some other languages,a token might be a single character or a syllable.The concept of tokens is crucial for two reasons:Processing text: when ChatGPT reads an input or generates an output, it doesso one token at a time. The model doesn%u2019t understand the text in the wayhumans do, but instead, it processes the probabilities of what token shouldcome next based on its training.Input and output limitations: ChatGPT models have a maximum limit of tokensthey can handle in a single request (both input and output). For instance, GPT3 has a maximum limit of 2,048 tokens (approximately ~1,500 words). Thismeans the total number of tokens, which includes the ones in the message youprovide (the prompt) and the ones in the message the model generates (theresponse), cannot exceed this limit.Understanding the concept of tokens can help you design more effectiveprompts. If a prompt is too long and takes up too many tokens, it might limitthe length of the response. On the other hand, if a prompt is too short andvague, the model may not generate a useful response. Balancing the length andprecision of your prompts is a key part of prompt engineering.n 6. 1. 2. The art of crafting a good promptCrafting an effective prompt for a language model like ChatGPT is both ascience and an art. A good prompt provides the model with the right amount ofcontext, clarity, and direction. Here are some key components to consider:181Crafting Effective Prompts for AI-Powered Prototyping