Four Key Tools for Robust Enterprise NLP with Yunyao Li

800 800 The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

About This Episode

Today we’re joined by Yunyao Li, a senior research manager at IBM Research.

Yunyao is in a somewhat unique position at IBM, addressing the challenges of enterprise NLP in a traditional research environment, while also having customer engagement responsibilities. In our conversation with Yunyao, we explore the challenges associated with productizing NLP in the enterprise, and if she focuses on solving these problems independent of one another, or through a more unified approach.

We then ground the conversation with real-world examples of these enterprise challenges, including enabling level document discovery at scale using combinations of techniques like deep neural networks and supervised and/or unsupervised learning, and entity extraction and semantic parsing to identify text. Finally, we talk through data augmentation in the context of NLP, and how we enable the humans in-the-loop to generate high-quality data.

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Thanks to our Sponsor!

Thanks to our friends at IBM for their continued support of the podcast, and their sponsorship of today’s show IBM Logo. With over 3,000 researchers across the globe, IBM Research is committed to turning fundamental research into impactful technologies that improves lives. Through research efforts like Project Debater, AI Fairness 360, and many more, IBM researchers continue to contribute to fundamental innovations in the field of artificial intelligence as well as practical applications for the technologies they develop.

To learn more about IBM’s interesting projects and the many ways they are working to solve today’s pressing needs, visit

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