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  2. PROMT - Wikipedia

    en.wikipedia.org/wiki/PROMT

    1991. ( 1991) Products. Neural machine translation systems. Website. www .promt .com. ProMT is a lead Russian developer of language translation software for businesses and private users since 1991. The company provides on-premises software based on neural technologies. [1]

  3. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    Prompt engineering is enabled by in-context learning, defined as a model's ability to temporarily learn from prompts. The ability for in-context learning is an emergent ability [14] of large language models. In-context learning itself is an emergent property of model scale, meaning breaks [15] in downstream scaling laws occur such that its ...

  4. Neural machine translation - Wikipedia

    en.wikipedia.org/wiki/Neural_machine_translation

    Neural machine translation ( NMT) is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model. It is the dominant approach today [1] : 293 [2] : 1 and can produce translations that rival human translations when ...

  5. ChatGPT - Wikipedia

    en.wikipedia.org/wiki/ChatGPT

    ChatGPT is a chatbot and virtual assistant developed by OpenAI and launched on November 30, 2022. Based on large language models (LLMs), it enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. Successive user prompts and replies are considered at each conversation stage as context.

  6. Comparison of machine translation applications - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_machine...

    Languages features comparison. The following table compares the number of languages which the following machine translation programs can translate between. (Moses and Moses for Mere Mortals allow you to train translation models for any language pair, though collections of translated texts (parallel corpus) need to be provided by the user.

  7. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    Prompt engineering, attention mechanism, and context window See also: Prompt engineering and Attention (machine learning) Most results previously achievable only by (costly) fine-tuning, can be achieved through prompt engineering , although limited to the scope of a single conversation (more precisely, limited to the scope of a context window).

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