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Multimodality is the application of multiple literacies within one medium. Multiple literacies or "modes" contribute to an audience's understanding of a composition. [ 1 ] Everything from the placement of images to the organization of the content to the method of delivery creates meaning.
t. e. Multimodal learning, in the context of machine learning, is a type of deep learning using multiple modalities of data, such as text, audio, or images. In contrast, unimodal models can process only one type of data, such as text (typically represented as feature vectors) or images. Multimodal learning is different from combining unimodal ...
Multimodal pedagogy is an approach to the teaching of writing that implements different modes of communication. [1][2] Multimodality refers to the use of visual, aural, linguistic, spatial, and gestural modes in differing pieces of media, each necessary to properly convey the information it presents. [3][4] The visual mode conveys meaning via ...
Multiliteracy (plural: multiliteracies) is an approach to literacy theory and pedagogy coined in the mid-1990s by the New London Group. [1] The approach is characterized by two key aspects of literacy – linguistic diversity and multimodal forms of linguistic expressions and representation. It was coined in response to two major changes in the ...
Application of Learning theory (education) to E-Learning (theory) As alluded to at the beginning of this section, the discussion of whether to use virtual or physical learning environments is unlikely to yield an answer in the current format. First, the efficacy of the learning environment may depend on the concept being taught. [71]
t. e. A large language model (LLM) is a computational model capable of language generation or other natural language processing tasks. As language models, LLMs acquire these abilities by learning statistical relationships from vast amounts of text during a self-supervised and semi-supervised training process. [1]
Multimodal models can either be trained from scratch, or by finetuning. A 2022 study found that Transformers pretrained only on natural language can be finetuned on only 0.03% of parameters and become competitive with LSTMs on a variety of logical and visual tasks, demonstrating transfer learning . [ 93 ]
Chinese, English, Russian. Type. Large language model. License. Proprietary. Huawei PanGu, PanGu, PanGu-Σ or PanGu-π (Chinese: 盘古大模型; pinyin: pángǔ dà móxíng) is a multimodal large language model developed by Huawei. It was announced on July 7, 2023, positioned as a contender to other multimodal large language models. [1]