Panel: NLP in Practice
If you read blog posts from tech giants, their most-cited academic papers, or major news stories about them, the current state of natural language seems to be a glorious thing, largely determined by a handful of top AI research teams in the world, and dominated by large ML models that can do almost anything imaginable.
However, if you have actual work to accomplish using NLP tools, and are held accountable to measures such as “return on investment” or “customer feedback” then you’re probably aware that the preceding sketch of the industry is abjectly false.
What is the current state of using NLP in practice? This panel, moderated by Paco Nathan and featuring technologists who’ve been building NLP apps in industry and government, cuts through the vendor marketing hype and explores the concerns from NLP practitioners’ perspective.
Known as a “player/coach”, with core expertise in data science, natural language, machine learning, cloud computing; 38+ years tech industry experience, ranging from Bell Labs to early-stage start-ups.
Amy Heineike is the Principal Product Architect at Primer, building machines that read and write text, leveraging NLP, NLG, and a host of algorithms to augment human analysts.
Joel Grus is Principal Engineer at Capital Group, where he leads a team that builds machine learning and data science products.
Felisia Loukou is a Senior Data Scientist at Adarga, specializing in metadata mining and knowledge discovery.
Daniel is a co-founder of Recognai, a company specializing in natural language processing and data science with unstructured data.