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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. WPS Office - Wikipedia

   en.wikipedia.org/wiki/WPS_Office

   WPS Office (an acronym for Writer, Presentation and Spreadsheets, [3] previously known as Kingsoft Office) is an office suite for Microsoft Windows, macOS, Linux, [4] iOS, [5] Android, [6] Fire OS and HarmonyOS [2] developed by Chinese software developer company, Kingsoft Office Software.

4. Blackboard system - Wikipedia

   en.wikipedia.org/wiki/Blackboard_system

   In this domain, the problem of integrating various AI algorithms into a single intelligent system arises spontaneously, with blackboards providing a way for a collection of distributed, modular natural language processing algorithms to each annotate the data in a central space, without needing to coordinate their behavior.

5. Neural network (machine learning) - Wikipedia

   en.wikipedia.org/wiki/Neural_network_(machine...

   This model paved the way for research to split into two approaches. One approach focused on biological processes while the other focused on the application of neural networks to artificial intelligence. In the late 1940s, D. O. Hebb [14] proposed a learning hypothesis based on the mechanism of neural plasticity that became known as Hebbian ...

6. Sora (text-to-video model) - Wikipedia

   en.wikipedia.org/wiki/Sora_(text-to-video_model)

   Several other text-to-video generating models had been created prior to Sora, including Meta's Make-A-Video, Runway's Gen-2, and Google's Lumiere, the last of which, as of February 2024, is also still in its research phase. [3]

7. Generative adversarial network - Wikipedia

   en.wikipedia.org/wiki/Generative_adversarial_network

   The generator is decomposed into a pyramid of generators =, with the lowest one generating the image () at the lowest resolution, then the generated image is scaled up to (()), and fed to the next level to generate an image (+ (())) at a higher resolution, and so on. The discriminator is decomposed into a pyramid as well.