Search results
Results from the WOW.Com Content Network
Create a list of [four] creative writing prompts for [high school] students. Use a mix of fiction and creative nonfiction prompts. Outline a lesson plan to teach [middle school] students about ...
The film opens with text explaining that the film's writing began with the ChatGPT prompt, "Write a plot for a film where a screenwriter realizes he is less good than artificial intelligence." The text explains that from there, the filmmakers used ChatGPT to write the film without alterations aside from shortening scenes.
6. Explain complex topics in new ways. Generative AI can even help you better understand the topics you’re writing about, especially if the tool you’re using is connected to the internet.
Matas also suggests a "user-centered design of the writing process" which prioritizes users over the technology. This "user-centered design" involves two core components. The first is an emphasis on reflective writing which would encourage students to view writing as a process rather than product-based like how ChatGPT can be.
Prompt engineering is the process of structuring an instruction that can be interpreted and understood by a generative artificial intelligence (AI) model. [1] [2] A prompt is natural language text describing the task that an AI should perform. [3]
On the SAT reading and writing section, GPT-4 scored a 710 out of 800, 40 points higher than GPT-3.5. On the SAT math section, GPT-4 scored 700, marking a 110 point increase from GPT-3.5.
ChatGPT is a generative artificial intelligence chatbot [2] [3] developed by OpenAI and launched in 2022. It is currently based on the GPT-4o large language model (LLM). ChatGPT can generate human-like conversational responses and enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. [4]
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.