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  2. DALL-E - Wikipedia

    en.wikipedia.org/wiki/DALL-E

    [64] [65] Released in 2022 on Hugging Face's Spaces platform, Craiyon (formerly DALL-E Mini until a name change was requested by OpenAI in June 2022) is an AI model based on the original DALL-E that was trained on unfiltered data from the Internet. It attracted substantial media attention in mid-2022, after its release due to its capacity for ...

  3. GPT-4o - Wikipedia

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

    On July 18, 2024, OpenAI released a smaller and cheaper version, GPT-4o mini. [ 18 ] According to OpenAI, its low cost is expected to be particularly useful for companies, startups, and developers that seek to integrate it into their services, which often make a high number of API calls.

  4. What is the DALL-E mini AI art generator that’s taking over ...

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  5. OpenAI - Wikipedia

    en.wikipedia.org/wiki/OpenAI

    Revealed in 2021, DALL-E is a Transformer model that creates images from textual descriptions. [231] DALL-E uses a 12-billion-parameter version of GPT-3 to interpret natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and generate corresponding images.

  6. OpenAI o3 - Wikipedia

    en.wikipedia.org/wiki/OpenAI_o3

    Reinforcement learning was used to teach o3 to "think" before generating answers, using what OpenAI refers to as a "private chain of thought". [10] This approach enables the model to plan ahead and reason through tasks, performing a series of intermediate reasoning steps to assist in solving the problem, at the cost of additional computing power and increased latency of responses.

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  8. Kristin Davis is looking back on her Melrose Place days.. In the latest PEOPLE cover story, the Sex and the City alum, 59, reflects on her storied career in television and gets candid about the ...

  9. Attention Is All You Need - Wikipedia

    en.wikipedia.org/wiki/Attention_Is_All_You_Need

    Image and video generators like DALL-E (2021), Stable Diffusion 3 (2024), [44] and Sora (2024), use Transformers to analyse input data (like text prompts) by breaking it down into "tokens" and then calculating the relevance between each token using self-attention, which helps the model understand the context and relationships within the data.

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