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Defining Key Terms
Throughout this support guide, I will refer to specific terms which have a place in AI and technology as a whole. If you see a term that you do not know the meaning of, you may want to come back to this section to look for the definition. I want to make this e-book as simple and user-friendly as possible using common language where possible.
Prompt - When creating an AI model, you need to tell it what you want it to do. This is the prompt. Think of the prompt as instructions. An example could be ‘Write me an introduction for a blog post based on the following information’.
Preset Models - This is where you are accessing an AI model via a third party for example Content Villain. You are using a model that has been pretrained based on the determination of the company you are using it through.
Model - Different companies offer different models for generating text. These can vary based on size (parameters) and also on the quality of the training data. Generally all models are in the billions of parameters size range. Size doesn’t necessarily mean best quality for all tasks however so digging a little deeper can be valuable.
Prompt Engineering - This term references where an AI model is created by providing a few examples within the prompt. This can also be referenced as ‘few shot learning’. You are expecting
Finetuning - The method of finetuning is when you provide an AI model with a large dataset of examples. By providing such a dataset, you are giving the AI a better understanding of what you are wanting it to output and can remove the need to prompt engineer. Generally speaking, finetuning will get you a better quality output if your dataset is of a good quality.
Datasets - Datasets are large files of text with multiple examples of your desired AI output and also the input text. An example dataset could look like the following; if you wanted a dataset for blog introductions, you could provide 50,000 examples of a blog title and brief description and also 50,000 examples of the blog introduction.
Tokens - Most companies offering AI Models work on tokens for pricing. Each token is similar to a syllable so a longer word may take multiple tokens to create. It is also important to understand that some companies include input tokens alongside output tokens in their pricing.