An open source platform for understanding, visualising, and auditing natural language processing (NLP) models for the third-party developers, Google AI researchers have made the Language Interpretability Tool (LIT). 

This tool has been especially designed and developed to focus on AI models to answer deep questions about their behavior. For instance, AI sometimes makes certain predictions which can be attributed to adversarial behaviour or also towards undesirable priors in the training set. 

Moreover, for entire data sets to spotlight patterns in model performance, it calculates and displays metrics. According to the team behind LIT, "In LIT's metrics table, we can slice a selection by pronoun type and by the true referent."

"LIT works with any model that can run from Python, the Google researchers say, including TensorFlow, PyTorch, and remote models on a server," reports VentureBeat.

Concerned with the interactions of natural human languages between computers, Natural Language Processing particularly concerns on how to programme computers so as to process and analyze large amounts of natural language data. 

In the near future, the Google LIT team has said, “The tool set will gain features like counterfactual generation plug-ins, additional metrics and visualizations for sequence and structured output types, and a greater ability to customise the user interface (UI) for different applications.”