We will discuss word embeddings this week. Word embeddings represent a fundamental shift in natural language processing (NLP) ...

Word embeddings are directly responsible for many of the exponential advancements natural language technologies have made over the past couple years. They’re foundational to the functionality of ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

In this video, we will learn about training word embeddings. To train word embeddings, we need to solve a fake problem. This ...

English look at AI and the way its text generation works. Covering word generation and tokenization through probability scores, to help ...

Bilingual word embeddings (BWEs) play a very important role in many natural language processing (NLP) tasks, especially cross-lingual tasks such as machine translation (MT) and cross-language ...

Vector similarity search uses machine learning to translate the similarity of text, images, or audio into a vector space, making search faster, more accurate, and more scalable. Suppose you wanted to ...