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Four Key Tools for Robust Enterprise NLP with Yunyao Li - #537
FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Four Key Tools for Robust Enterprise NLP with Yunyao Li - #537
FromThe TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
ratings:
Length:
58 minutes
Released:
Nov 18, 2021
Format:
Podcast episode
Description
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.
The complete show notes for this episode can be found at twimlai.com/go/537
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.
The complete show notes for this episode can be found at twimlai.com/go/537
Released:
Nov 18, 2021
Format:
Podcast episode
Titles in the series (100)
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