encoder-decoder model
[en-KOH-der dih-KOH-der MAH-dul]
nounpl: encoder-decoder models
modelo codificador-decodificador
1. A neural network architecture consisting of two main components: an encoder that processes input data and compresses it into a context vector, and a decoder that generates output data from this representation
The encoder-decoder model is widely used in machine translation tasks to convert text from one language to another.
O modelo codificador-decodificador é amplamente utilizado em tarefas de tradução automática para converter texto de um idioma para outro.
2. An artificial intelligence framework commonly applied to sequence-to-sequence problems such as machine translation, image captioning, and speech recognition
Google's translation service relies on encoder-decoder models with attention mechanisms to improve translation quality.
O serviço de tradução do Google utiliza modelos codificador-decodificador com mecanismos de atenção para melhorar a qualidade da tradução.
This term is primarily used in technical and academic contexts within the AI/machine learning field. It originated in Silicon Valley research communities and is now standard terminology in both Brazilian and international tech industries. The concept became particularly prominent after the introduction of transformer-based models like BERT and GPT, though encoder-decoder architectures remain foundational in machine learning education and research.
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