March 31, 2021
In this video Justin Pounders, Director of Machine Learning and AI Research at Prolego, breaks down natural language generation (NLG) into its most basic components and describes how you can begin building out these components in your business. (And, no, it doesn’t depend on GPT-3!) He describes how NLG depends critically on two questions (WHAT you want to say and HOW you say it), the types of data you can feed into NLG systems, and a development path for being able to summarize multiple sources of data in plain English.
March 30, 2021
Like most engineers, I hate tedious work. That’s why I love the idea of automatic machine learning (AutoML). As much as I want to love AutoML, it’s been incorrectly framed as a substitute for data scientists. This confusion arises from a misunderstanding of what actually happens in machine learning projects.
March 24, 2021
Document analysis and understanding is an active area of research in the applied NLP community. In this talk, we demonstrate an unsupervised method to organize a body of text into a set of topics and outliers. This approach uses a transformer model that has been fine-tuned for semantic similarity (SentenceTransformers hyperlink: sbert.net). It can be used to quickly review a large set of documents to identify areas of interest or concern without requiring a human to exhaustively read through each document one-by-one. We demonstrate this approach applied to the lyrics of an early-2000s hit musical piece.