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The essay is to consist of an introduction three or more sentences long and containing a thesis statement, a conclusion incorporating all the writer's commentary and bringing the essay to a close, and two or three body paragraphs; Schaffer herself preferred to teach a four-paragraph essay rather than the traditional five-paragraph essay.
Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.
The five-paragraph essay is a form of essay having five paragraphs: one introductory paragraph, three body paragraphs with support and development, and; one concluding paragraph. The introduction serves to inform the reader of the basic premises, and then to state the author's thesis, or central idea.
Generative AI systems such as MusicLM [72] and MusicGen [73] can also be trained on the audio waveforms of recorded music along with text annotations, in order to generate new musical samples based on text descriptions such as a calming violin melody backed by a distorted guitar riff.
A text-to-image prompt commonly includes a description of the subject of the art, the desired medium (such as digital painting or photography), style (such as hyperrealistic or pop-art), lighting (such as rim lighting or crepuscular rays), color, and texture. [51] Word order also affects the output of a text-to-image prompt.
Its structure normally builds around introduction with a topic's relevance and a thesis statement, body paragraphs with arguments linking back to the main thesis, and conclusion. In addition, an argumentative essay may include a refutation section where conflicting ideas are acknowledged, described, and criticized.
These expert systems closely resembled modern question answering systems except in their internal architecture. Expert systems rely heavily on expert-constructed and organized knowledge bases, whereas many modern question answering systems rely on statistical processing of a large, unstructured, natural language text corpus.
By adjusting the "image weight" parameter, users can prioritize either the content of the prompt or the characteristics of the image. For instance, setting a higher weight will ensure that the generated result closely follows the image's structure and details, while a lower weight allows the text prompt to have more influence over the final output.