What are the applications of embeddings in AI?

What are the applications of embeddings in AI?

Embeddings are used in various AI applications, including natural language processing, image recognition, and recommendation systems.

Can you explain how embeddings work in natural language processing?

In NLP, embeddings convert words into numerical vectors, capturing semantic meanings and relationships between words.

What are some popular embedding techniques?

Popular techniques include Word2Vec, GloVe, and more recently, contextual embeddings like BERT and ELMo.

How do embeddings improve recommendation systems?

Embeddings help in representing users and items in a shared space, allowing for better similarity measurements and recommendations.

Are there any limitations to using embeddings?

Yes, embeddings can sometimes capture biases present in the training data and may not generalize well to unseen data.