Four Key Tools for Robust Enterprise NLP with Yunyao Li

EPISODE 537
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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 IBM

The IBM Institute for Business Value (IBV) delivers trusted business insights from our position at the intersection of technology and business, combining expertise from industry thinkers, leading academics, and subject matter experts with global research and performance data. The IBV thought leadership portfolio includes research deep dives, benchmarking and performance comparisons, and data visualizations that support business decision making across regions, industries and technologies.
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