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  1. 30 lis 2022 · ChatGPT is a sibling model to InstructGPT, which is trained to follow an instruction in a prompt and provide a detailed response. We are excited to introduce ChatGPT to get users’ feedback and learn about its strengths and weaknesses. During the research preview, usage of ChatGPT is free. Try it now at chatgpt.com. Samples. Fix code. Home security.

  2. chatgpt.comChatGPT

    ChatGPT helps you get answers, find inspiration and be more productive. It is free to use and easy to try. Just ask and ChatGPT can help with writing, learning, brainstorming and more.

  3. 6 lis 2023 · GPTs are a new way for anyone to create a tailored version of ChatGPT to be more helpful in their daily life, at specific tasks, at work, or at home—and then share that creation with others. For example, GPTs can help you learn the rules to any board game, help teach your kids math, or design stickers.

  4. 25 wrz 2023 · ChatGPT can now see, hear, and speak. We are beginning to roll out new voice and image capabilities in ChatGPT. They offer a new, more intuitive type of interface by allowing you to have a voice conversation or show ChatGPT what you’re talking about. Voice and image give you more ways to use ChatGPT in your life.

  5. A generative pre-trained transformer (GPT) is a type of large language model (LLM) [ 1 ][ 2 ][ 3 ] and a prominent framework for generative artificial intelligence. [ 4 ][ 5 ] It is an artificial neural network that is used in natural language processing by machines. [ 6 ] .

  6. 20 maj 2023 · How different GPT models are implemented. At the time of writing, the three latest text generation models released by OpenAI are GPT-3.5, ChatGPT, and GPT-4, and they are all based on the Transformer architecture. In fact, “GPT” stands for “Generative Pre-trained Transformer.”

  7. GPT is a Transformer-based architecture and training procedure for natural language processing tasks. Training follows a two-stage procedure. First, a language modeling objective is used on the unlabeled data to learn the initial parameters of a neural network model.

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