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Unsupervised Text Analytics based NLP Architect

Aug 1, 2018 @ 1:00 pm - 2:30 pm

Unsupervised Text Analytics based NLP Architect

SPEAKER:  Moshe Wasserblat



Deep Learning, powerful computing resources and greater access to useful data sets drive many advances in AI in recent years. Still, it’s challenging to deploy and build AI solutions for the real world – Latest report showed that 85% of C-level executives believe that AI provides a competitive advantage but only 20% had incorporated AI into their solution (MITSloan).

Among the top challenges are the lack of interpretability, the need for a high cost ML/DL experts, domain dependency and the need for large amount of annotated data. In this session, we will present Intel’s Text-Analytics solutions to make AI NLP easy to deploy in business environment. The solutions are built on top of “NLP Architect”, an open source library recently released, and have the following merits: Explainable, End-to-End flow with simple UI, and Semi/Un-supervised.


Moshe Wasserblat is currently the Natural Language Processing and Deep Learning Research Group Manager for Intel’s Artificial Intelligence Products Group. In his former role, he has been with NICE Systems for more than 17 years, where he founded and led the Speech/Text Analytics Research team. His interests are in the field of speech processing and natural language processing. He was the co-founder coordinator of the EXCITEMENT FP7 ICT program and served as organizer and manager of several initiatives, including many Israeli Chief Scientist programs. He has filed more than 60 patents in the field of Language Technology and also has several publications in international conferences and journals. His areas of expertise include: Speech Recognition, Conversational Natural Language Processing, Emotion Detection, Speaker Separation, Speaker Recognition, Deep Learning, and Machine Learning.



WEB/CONFERENCECALL INFO: We are going to use the NC State WebEx for the web conference.Please note that this WebEx belongs to NC State and can not be downloadeddirectly from Cisco. Also, it should work on iPhones and iPads via the WebExApp. A good internet connection is recommended. For better audio, please joinvia computer and then have the meeting call your number or call in directlyusing one of the numbers below. When not speaking, please mute your phone toavoid background noise. When it’s time, join the WebEx meeting from here:




919-513-9329 (WolfMeeting)

Access Code: 996 474 981



Aug 1, 2018
1:00 pm - 2:30 pm


Partners I, 1017 Main Campus Dr, Raleigh, NC 27606, USA
800 Main Campus Dr United States



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LAS aims to bring together a multi-disciplinary group of academic, industry, and government researchers, analysts and managers together to re-engineer the intelligence analysis process to promote predictive analysis. LAS will do this by conducting both classified and unclassified research in a variety of areas of research. The research done in this area will serve as the foundation for mission effects and integrated back into the enterprise.

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