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  2. ChatGPT - Wikipedia

    en.wikipedia.org/wiki/ChatGPT

    ChatGPT was released as a freely available research preview, but due to its popularity, OpenAI now operates the service on a freemium model. Users on its free tier can access GPT-4o and GPT-3.5. The ChatGPT subscriptions "Plus", "Team" and "Enterprise" provide additional features such as DALL-E 3 image generation and increased GPT-4o usage limit.

  3. ChatGPT can now respond with spoken words. But what is it ...

    www.aol.com/news/chatgpt-used-exactly-does-heres...

    Currently, you can use a basic version of ChatGPT for free at chat.openai.com, or update to ChatGPT Plus for $20 a month for access to ChatGPT-4, the latest model with the fastest response speed.

  4. OpenAI - Wikipedia

    en.wikipedia.org/wiki/OpenAI

    Google announced a similar AI application , after ChatGPT was launched, fearing that ChatGPT could threaten Google's place as a go-to source for information. On February 7, 2023, Microsoft announced that it was building AI technology based on the same foundation as ChatGPT into Microsoft Bing, Edge, Microsoft 365 and other products.

  5. A dietitian tried ChatGPT’s free, custom meal planner ... - AOL

    www.aol.com/news/m-dietitian-asked-chatgpt-meal...

    To consistently reach 1,700 calories each day, add a small, healthy snack to each day’s plan: Day 1: Add an additional 50-calorie snack (e.g., a few more almonds, an extra piece of fruit or a ...

  6. Apple announces deal with OpenAI. Will it be a game-changer?

    www.aol.com/news/apple-announces-deal-openai...

    This allows Apple to harness ChatGPT's platform and in return, Apple users also become familiar with ChatGPT and what it can do. Every day, Apple said, Siri gets 1.5 billion voice requests.

  7. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    History Initial developments. Generative pretraining (GP) was a long-established concept in machine learning applications. 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.

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