Neural Machine Translation (NMT) has made significant strides in language translation, yet key challenges remain. NMT models often struggle with contextual nuances, idiomatic expressions, and specialized terminology, leading to inaccurate translations. Additionally, resource-heavy models limit their scalability, especially for low-resource languages.
At NeuraCore Labs, we are dedicated to improving NMT by enhancing translation accuracy, reducing computational costs, and ensuring broader language support. Our research aims to create more efficient, reliable, and contextually aware translation systems for the future.