An activity in which computers are entailed to analyze, understand, alter, or generate natural language. This includes the automation of any or all linguistic forms, activities, or methods of communication, such as conversation, correspondence, reading, written composition, dictation, publishing, translation, lip reading, and so on. Natural language processing is also the name of the branch of computer science, artificial intelligence, and linguistics concerned with enabling computers to engage in communication using natural language(s) in all forms, including but not limited to speech, print, writing, and signing.

GPT2 using Mathematica and MXNet

A large-scale unsupervised language model which generates coherent paragraphs of text, achieves state-of-the-art performance on many language modeling benchmarks, and performs rudimentary reading comprehension, machine translation, question answering, and summarization—all without task-specific training.

Training classifiers with natural language explanations

Somewhat similar to Spacy's Prodigy, the BabbleLabble use natural language to train a labeler.

Textual entailment

How logical consequences can be understood in NLP.

The classic NLU toolkit

Intro Traditionally, work in natural language processing has tended to view the process of language analysis as being decomposable into a number of stages, mirroring the theoretical linguistic distinctions drawn between SYNTAX, SEMANTICS, and…

Approaches to NLU

Why is language so complex? Percy Liang, a Stanford NLP expert, breaks down the various approaches to NLU into four distinct categories: Distributional Frame-based Model-theoretical Interactive learning You might appreciate a brief linguistics…