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  2. Google Neural Machine Translation - Wikipedia

    en.wikipedia.org/wiki/Google_Neural_Machine...

    Google Translate's NMT system uses a large artificial neural network capable of deep learning. [1] [2] [3] By using millions of examples, GNMT improves the quality of translation, [2] using broader context to deduce the most relevant translation.

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

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

    Sora is a text-to-video model developed by OpenAI. The model generates short video clips based on user prompts, and can also extend existing short videos. Sora was released publicly for ChatGPT Plus and ChatGPT Pro users in December 2024. [1] [2]

  4. Neural machine translation - Wikipedia

    en.wikipedia.org/wiki/Neural_machine_translation

    A generative LLM can be prompted in a zero-shot fashion by just asking it to translate a text into another language without giving any further examples in the prompt. Or one can include one or several example translations in the prompt before asking to translate the text in question. This is then called one-shot or few-shot learning, respectively.

  5. Google reveals AR glasses that can translate speech in real ...

    www.aol.com/finance/google-reveals-ar-glasses...

    The demo showed how Google’s Translate can automatically listen to speech and translate it in real-time, displaying the translated text for the wearer to see and read with ease.

  6. Otter.ai - Wikipedia

    en.wikipedia.org/wiki/Otter.ai

    Otter.ai, Inc. is an American transcription software company based in Mountain View, California. The company develops speech to text transcription applications using artificial intelligence and machine learning. Its software, called Otter, shows captions for live speakers, and generates written transcriptions of speech. [1]

  7. Machine translation - Wikipedia

    en.wikipedia.org/wiki/Machine_translation

    Machine translation is use of computational techniques to translate text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages. Early approaches were mostly rule-based or statistical. These methods have since been superseded by neural machine translation [1] and large language models ...

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