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  2. GPT-4o - Wikipedia

    en.wikipedia.org/wiki/GPT-4o

    It has a context length of 128k tokens [15] with an output token limit capped to 4,096, [16] and after a later update (gpt-4o-2024-08-06) to 16,384. [ 17 ] As of May 2024, it is the leading model in the LMSYS Elo Arena Benchmarks by the University of California, Berkeley .

  3. GPT-4 - Wikipedia

    en.wikipedia.org/wiki/GPT-4

    Generative Pre-trained Transformer 4 (GPT-4) is a multimodal large language model trained and created by OpenAI and the fourth in its series of GPT foundation models. [1] It was launched on March 14, 2023, [1] and made publicly available via the paid chatbot product ChatGPT Plus, via OpenAI's API, and via the free chatbot Microsoft Copilot. [2]

  4. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    Other models with large context windows includes Anthropic's Claude 2.1, with a context window of up to 200k tokens. [46] Note that this maximum refers to the number of input tokens and that the maximum number of output tokens differs from the input and is often smaller. For example, the GPT-4 Turbo model has a maximum output of 4096 tokens. [47]

  5. OpenAI unveils newest AI model, GPT-4o - AOL

    www.aol.com/openai-unveils-newest-ai-model...

    OpenAI executives demonstrated a spoken conversation with ChatGPT to get real-time instructions for solving a math problem, to tell a bedtime story and to get coding advice.

  6. Generative pre-trained transformer - Wikipedia

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

    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.

  7. Multimodal learning - Wikipedia

    en.wikipedia.org/wiki/Multimodal_learning

    Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images, or video.This integration allows for a more holistic understanding of complex data, improving model performance in tasks like visual question answering, cross-modal retrieval, [1] text-to-image generation, [2] aesthetic ranking, [3] and ...

  8. Llama (language model) - Wikipedia

    en.wikipedia.org/wiki/Llama_(language_model)

    Llama 2 – Chat models were derived from foundational Llama 2 models. Unlike GPT-4 which increased context length during fine-tuning, Llama 2 and Code Llama - Chat have the same context length of 4K tokens. Supervised fine-tuning used an autoregressive loss function with token loss on user prompts zeroed out. The batch size was 64.

  9. OpenAI o3 - Wikipedia

    en.wikipedia.org/wiki/OpenAI_o3

    OpenAI o3 is a reflective generative pre-trained transformer (GPT) model developed by OpenAI as a successor to OpenAI o1. It is designed to devote additional deliberation time when addressing questions that require step-by-step logical reasoning. [1] [2] OpenAI released the smaller model, o3-mini, on January 31st, 2025. [3]