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  2. Teachers sound off on ChatGPT, the new AI tool that can write ...

    www.aol.com/teachers-sound-off-chatgpt-ai...

    To confirm his suspicions, Hick says he ran passages from the essay through a separate OpenAI detector, which indicated the writing was AI-generated. Hick then did the same thing with essays from ...

  3. Teachers, students test out AI in Colorado classrooms

    www.aol.com/teachers-students-test-ai-colorado...

    Generative AI analyzes huge amounts of data to generate text, images, videos, and other kinds of content. ... taking a first pass at grading essays, or writing and translating parent newsletters ...

  4. Teachers are using AI to grade essays. But some experts are ...

    www.aol.com/teachers-using-ai-grade-essays...

    teaching ChatGPT best practices in her writing workshop class at the University of Lynchburg in Virginia, said she sees the advantages for teachers using AI tools but takes issue with how it can ...

  5. Apple Intelligence - Wikipedia

    en.wikipedia.org/wiki/Apple_Intelligence

    Apple Intelligence features writing tools that are powered by AI, including Rewrite, and Proofread. These features help enhance users' writing to make it more friendly, concise or professional, similar to Grammarly's AI writing features. It can also be used to generate summaries, key points, tables, and lists from an article or piece of writing.

  6. GPT-3 - Wikipedia

    en.wikipedia.org/wiki/GPT-3

    GPT-3 was used by The Guardian to write an article about AI being harmless to human beings. It was fed some ideas and produced eight different essays, which were ultimately merged into one article. [44] GPT-3 was used in AI Dungeon, which generates text-based adventure games. Later it was replaced by a competing model after OpenAI changed their ...

  7. Attention Is All You Need - Wikipedia

    en.wikipedia.org/wiki/Attention_Is_All_You_Need

    Transformer architecture is now used in many generative models that contribute to the ongoing AI boom. In language modelling, ELMo (2018) was a bi-directional LSTM that produces contextualized word embeddings, improving upon the line of research from bag of words and word2vec. It was followed by BERT (2018), an encoder-only Transformer model. [33]