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  2. Generative artificial intelligence - Wikipedia

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

    Generative AI can also be trained extensively on audio clips to produce natural-sounding speech synthesis and text-to-speech capabilities, exemplified by ElevenLabs' context-aware synthesis tools or Meta Platform's Voicebox. [55] AI-generated music from the Riffusion Inference Server, prompted with bossa nova with electric guitar

  3. Microsoft PowerPoint - Wikipedia

    en.wikipedia.org/wiki/Microsoft_PowerPoint

    In contemporary operation, PowerPoint is used to create a file (called a "presentation" or "deck") containing a sequence of pages (called "slides" in the app) which usually have a consistent style (from template masters), and which may contain information imported from other apps or created in PowerPoint, including text, bullet lists, tables ...

  4. Adobe Presenter - Wikipedia

    en.wikipedia.org/wiki/Adobe_Presenter

    The main purpose of Adobe Presenter is to capture on-screen presentations and convert them into more interactive and engaging videos. Support is given to convert Microsoft PowerPoint 2010 and 2013 presentations into videos. It also allows for content authoring on PowerPoint and ActionScript 3, and offers integration with Adobe Captivate. Slide ...

  5. iSpring Suite - Wikipedia

    en.wikipedia.org/wiki/ISpring_Suite

    iSpring Suite is a PowerPoint-based authoring toolkit produced by iSpring Solutions that allows users to create slide-based courses, quizzes, dialog simulations, screencasts, video lectures, and other interactive learning materials.

  6. DALL-E - Wikipedia

    en.wikipedia.org/wiki/DALL-E

    DALL-E was revealed by OpenAI in a blog post on 5 January 2021, and uses a version of GPT-3 [5] modified to generate images.. On 6 April 2022, OpenAI announced DALL-E 2, a successor designed to generate more realistic images at higher resolutions that "can combine concepts, attributes, and styles". [6]

  7. 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 .

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