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2. Generative artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Generative_artificial...

   Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 2 ] [ 3 ] [ 4 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 5 ] [ 6 ] based on ...

3. 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 a smaller model, o3-mini, on January 31st, 2025. [3]

4. Midjourney - Wikipedia

   en.wikipedia.org/wiki/Midjourney

   Midjourney is a generative artificial intelligence program and service created and hosted by the San Francisco-based independent research lab Midjourney, Inc. Midjourney generates images from natural language descriptions, called prompts, similar to OpenAI's DALL-E and Stability AI's Stable Diffusion. [1] [2] It is one of the technologies of ...

5. PDFescape - Wikipedia

   en.wikipedia.org/wiki/PDFescape

   PDFescape is an advertising- and fee-supported PDF editor program written in JavaScript, HTML, CSS and ASP. It has an online and Windows version. It features PDF editing, form filling, page arrangement, printing, saving, and form publishing. A premium ad free version is available for a fee. Form publishing requires additional fees.

6. California to tap generative AI tools to increase services ...

   www.aol.com/news/california-tap-generative-ai...

   The state is partnering with five companies to create generative AI tools using technologies developed by tech giants such as Microsoft-backed OpenAI and Google-backed Anthropic that would ultimate.

7. Retrieval-augmented generation - Wikipedia

   en.wikipedia.org/wiki/Retrieval-augmented_generation

   Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.