That's just scratching the surface, but it gives you an idea of what we're looking at here. Most AI text generators also offer a text editor, where you can edit the AI-generated text directly from the app. It would have you indicate the content type, let you select the length, choose a tone from a dropdown menu, and so on. In an AI text generator, you'd get prompted for all that information. For example, you'd type: "Write a 150-word email in a friendly tone to a customer about the new matching human/dog outfits offered by Winston.ly." In ChatGPT, if you wanted to write a 150-word email in a friendly tone to a customer about your new product feature, you'd need to type that all right into ChatGPT. It's nothing you can't do in ChatGPT, but it's presented in a way that makes sure you don't forget any important details, helping you get the best output possible. What most of these AI text generator apps do, then, is add a user interface on top of GPT that allows you to control its output. It's wild how much work has gone into it-and how little we understand about how these algorithms really work. Basically, GPT has crunched through the sum total of human knowledge and built a deep learning neural network-a complex, many-layered, weighted algorithm modeled after the human brain. That training data includes books, articles, and other documents across all different topics, styles, and genres-and an unbelievable amount of content scraped from the open internet. GPT works by taking a text prompt and then predicting what words will best follow on from your request, based on the data it was trained on. Since most text generation apps rely on GPT-and GPT itself is based on the transformer architecture that Google developed and uses in LaMDA-let's hone in on how GPT works, so you can have a rough idea as to what's going on under the hood with these language models.
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