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2. Text-to-video model - Wikipedia

   en.wikipedia.org/wiki/Text-to-video_model

   A text-to-video model is a machine learning model that uses a natural language description as input to produce a video relevant to the input text. [1] Advancements during the 2020s in the generation of high-quality, text-conditioned videos have largely been driven by the development of video diffusion models .

3. 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 ...

4. TikTok will automatically label AI-generated content on the ...

   www.aol.com/news/tiktok-automatically-label-ai...

   Still, companies hope to pair watermarking with education on AI. Alongside the new AI tags, TikTok will be producing 12 videos promoting and teaching media literacy skills in collaboration with ...

5. Text-to-image model - Wikipedia

   en.wikipedia.org/wiki/Text-to-image_model

   An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.

6. Hitler’s AI translated speeches go viral on TikTok - AOL

   www.aol.com/news/hitler-ai-translated-speeches...

   An account with more than 20,000 followers and nearly 4 million views of 12 videos with Hitler speeches, an outline of Hitler and text that states, “Growing up is realizing Who the villain ...

7. Text-to-image personalization - Wikipedia

   en.wikipedia.org/wiki/Text-to-image_personalization

   Text-to-Image personalization is a task in deep learning for computer graphics that augments pre-trained text-to-image generative models. In this task, a generative model that was trained on large-scale data (usually a foundation model ), is adapted such that it can generate images of novel, user-provided concepts.