Contextual embeddings

Contextual embeddings are a way for computers to understand words better by considering the surrounding words in a sentence. Instead of giving each word a fixed meaning, they generate dynamic representations that change depending on the context. For example, the word "bank" would have different embeddings when used in "river bank" versus "financial bank." This approach helps machines grasp subtle differences in meaning and improves tasks like translation, sentiment analysis, and chatbots. Essentially, contextual embeddings allow computers to interpret language more like humans do, by understanding how words relate to their specific situation.