Encoder-decoder architectures

Encoder-decoder architectures are a type of neural network used in tasks like language translation or summarization. The encoder processes and summarizes the input data—such as a sentence—into a compact, meaningful representation. The decoder then takes this representation and generates the desired output, like translating the sentence into another language. Think of it as a two-step process: first understanding and condensing information, then reconstructing or transforming it into a new form. This approach helps computers handle complex tasks involving sequences and transformations effectively.