Linguistic Annotation

Large language models show incredible capabilities. Learn about the technology behind them and how they came to be the powerful machines they are today.

Discover how a potential AI training data shortage for language models could affect your business, and what you can do to offset its impact.

There are a wide variety of audio transcription services. In this article, we’ll help you to figure out which type of audio transcription is best for you.

Learn about how data scientists use large volumes of annotated data to improve the decision-making of AI models.

Voice assistants are more prominent than ever. Discover five text annotation services to help you build an industry-leading voice assistant.

In this introduction to sentiment analysis, we discuss what it is, how it works, and offer advice for building a sentiment analysis model.

Covering everything from the basic makeup of an entity to popular formatting methods, this entity extraction guide will help you with your next AI data project.

Natural language processing (NLP) is the term used to describe a machine’s ability to interpret and respond to language data. Learn why it is a key AI concept.

Sentiment analysis involves classifying the subjective, contextual information within text data. Read our beginner’s guide to learn more.

Take an in-depth look at one particular use case of natural language processing that is founnd in many people’s daily lives: voice assistants.

Although many people use the terms text mining and text analytics interchangeably, there are key differences. Learn what text mining is, the processessing techniques used and its practical applications.

Take a look at why a global approach to NLP is so important for the future of machine learning in non-English languages.