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

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

    Re-captioning is used to augment training data, by using a video-to-text model to create detailed captions on videos. [ 7 ] OpenAI trained the model using publicly available videos as well as copyrighted videos licensed for the purpose, but did not reveal the number or the exact source of the videos. [ 5 ]

  3. OpenAI says it’s working on AI that mimics human voices - AOL

    www.aol.com/openai-says-working-ai-mimics...

    The preview of Voice Engine comes as users await the public release of Sora, the AI-generated video tool that OpenAI teased last month. Sora can create realistic looking 60-second videos from text ...

  4. Text-to-video model - Wikipedia

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

    Fliki AI 2022 Released Text-to-video with AI avatars and voices, extensive language and voice support [40] Supports 65+ AI avatars and 2,000+ voices in 70 languages [40] Free plan available, Paid plans starting at $30/month Varies based on subscription 70+ Runway Gen-2 Runway AI 2023 Released Multimodal video generation from text, images, or ...

  5. Artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence

    Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]

  6. Elon Musk secretly working on AI project with DeepMind ... - AOL

    www.aol.com/news/elon-musk-secretly-working-ai...

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  7. fast.ai - Wikipedia

    en.wikipedia.org/wiki/Fast.ai

    In 2018, students of fast.ai participated in the Stanford’s DAWNBench challenge alongside big tech companies such as Google and Intel.While Google could obtain an edge in some challenges due to its highly specialized TPU chips, the CIFAR-10 challenge was won by the fast.ai students, programming the fastest and cheapest algorithms.

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