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  2. Microsoft Copilot - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Copilot

    Copilot utilizes the Microsoft Prometheus model. According to Microsoft, this uses a component called the Orchestrator, which iteratively generates search queries, to combine the Bing search index and results [86] with OpenAI's GPT-4, [87] [88] GPT-4 Turbo, [89] and GPT-4o [90] foundational large language models, which have been fine-tuned ...

  3. Capella (engineering) - Wikipedia

    en.wikipedia.org/wiki/Capella_(engineering)

    Capella was created by Thales in 2007, and has been under continuous development and evolution since then. The objective is to contribute to the transformation of engineering, providing an engineering environment which approach is based on models rather than focused on documents, piloted by a process, and offering, by construction, ways to ensure effective co-engineering.

  4. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text. The largest and most capable LLMs are generative pretrained transformers (GPTs).

  5. Llama (language model) - Wikipedia

    en.wikipedia.org/wiki/Llama_(language_model)

    On July 18, 2023, in partnership with Microsoft, Meta announced LLaMa 2, the next generation of Llama. Meta trained and released Llama 2 in three model sizes: 7, 13, and 70 billion parameters. [7] The model architecture remains largely unchanged from that of LLaMA-1 models, but 40% more data was used to train the foundational models. [26]

  6. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    Like earlier seq2seq models, the original transformer model used an encoder-decoder architecture. The encoder consists of encoding layers that process all the input tokens together one layer after another, while the decoder consists of decoding layers that iteratively process the encoder's output and the decoder's output tokens so far.

  7. List of SysML tools - Wikipedia

    en.wikipedia.org/wiki/List_of_SysML_tools

    Commercial. Free education edition, subscription model Java MagicDraw: No Magic, a Dassault Systèmes company Windows, Windows Server, Linux, Mac OS X (Java SE 11-compatible) [12] 1998 2022-07-01 (2022x) [13] No Commercial Java Microsoft Visio: Microsoft: Windows 1992 2016 (v16.0) No Commercial Un­known Modelio: Modeliosoft (SOFTEAM Group)

  8. BERT (language model) - Wikipedia

    en.wikipedia.org/wiki/BERT_(language_model)

    It uses the encoder-only transformer architecture. It is notable for its dramatic improvement over previous state-of-the-art models, and as an early example of a large language model . As of 2020 [update] , BERT is a ubiquitous baseline in natural language processing (NLP) experiments.

  9. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.