Natural language processing (NLP) denotes the use of artificial intelligence (AI) to manipulate written or spoken languages. Like the air we breathe, NLP is so pervasive today that we hardly notice it ...

What Is Natural Language Processing? Natural language processing (NLP) “is a type of AI focused on teaching computers how to speak and understand text in the same way humans can,” Dobrin says. Voice ...

Natural language processing (NLP) is a branch of artificial intelligence (AI) involving the ability of computers to understand spoken language and text.

Natural language processing is a subfield of artificial intelligence and linguistics that focuses on developing techniques for computers to process, understand, interpret and generate human languages.

Teaching computers to make sense of human language has long been a goal of computer scientists. Natural language processing algorithms aim to make sense of it.

Natural language processing (NLP) and speech processing at RIT is a research-active area led by Dr. Cecilia Alm’s and Dr. Marcos Zampieri’s laboratories. The groups’ research projects, supported by ...

Learn the basics about natural language processing, a cross-discipline approach to making computers hear, process, understand, and duplicate human speech.

Clement Delangue is the co-founder and CEO of Hugging Face, a startup focused on natural language processing that has raised more than $20M. The company created Transformers, the fastest growing ...

Artificial Intelligence (AI) is revolutionizing many sectors, including scientific research. Language Model Learners (LLMs), ...

Natural language processing has been applied to numerous conditions in the past, but this is one of the first papers that applies it to social determinants of health.

Among these advancements, the popularity of diffusion language models has garnered significant attention. What exactly is a diffusion language model? Why has it sparked such great interest in a short ...

Clinical-grade NLP is in the earlier stages of adoption, but as healthcare organizations continue to struggle with unstructured data and clinician burnout, we will see a gradual increase in its ...