Human languages are known to have grown and changed considerably over the course of history, often reflecting technological, ...

Researchers from Fudan, Harvard, and Stony Brook University used AI and statistical analysis to study the evolution of 22 languages, uncovering a universal statistical structure underlying their ...

This post explores how bias can creep into word embeddings like word2vec, and I thought it might make it more fun (for me, at least) if I analyze a model trained on what you, my readers (all three of ...

Word embeddings also affect the ability to tailor language generation models to select responses from a particular source. Because they provide the means of models understanding what users are asking ...

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 ...

This study presents valuable findings by reanalyzing previously published MEG and ECoG datasets to challenge the predictive nature of pre-onset neural encoding effects. The evidence supporting the ...

Back in 2013, a handful of researchers at Google set loose a neural network on a corpus of three million words taken from Google News texts. The neural net’s goal was to look for patterns in the way ...