AI & Deep Learning
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Date: October 17, 2019
Time: 9:00am – 10:00am PT
Duration: 1 hour

Natural Language Processing (NLP) is a critical part of building better chatbots and AI assistants. Among the numerous language models used in NLP-based applications, BERT has emerged as a leader due to its innovative use of machine learning, rapid iteration and ease of use. Recently, NVIDIA shattered several records for speed in training BERT on the AI platform.

Join NVIDIA and Passage AI as they share insights on the breakthroughs in BERT training and how embedding BERT in their conversational AI bots will help aid in accuracy and utility. Unlock the potential for billions of expected conversational AI services arriving in the coming years to operate with human-level comprehension.

By attending this webinar, you'll learn:
  • Better understanding of deep learning techniques for Natural Language Processing (NLP).
  • How the BERT language model is used for NLP.
  • How deep learning techniques and NLP are making conversational AI a reality.



You will receive an email with instructions on how to join the webinar shortly.

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Yi Dong

Deep Learning Solutions Architect, NVIDIA

Yi Dong is a Deep Learning Solutions Architect at NVIDIA providing Financial Service Industry AI solutions. Yi received his Ph.D. from The Johns Hopkins University School of Medicine in computational neuroscience. Yi has 10 years of working experience in computer software engineering, machine learning, and finance. Yi likes reading about science and technology, especially the topic of intelligence, either artificial intelligence or biological intelligence.

Mitul Tiwari

CTO and Co-Founder, Passage AI

Mitul Tiwari expertise lies in building data-driven products using AI, machine learning, and big data technologies. Previously, he was head of People You May Know and Growth Relevance at LinkedIn, where he led technical innovations in large-scale social recommender systems. Prior to that, he worked at Kosmix (now Walmart Labs) on web-scale document and query categorization, and its applications. He earned his PhD in Computer Science from the University of Texas at Austin and his undergraduate degree from the Indian Institute of Technology, Bombay. He has also co-authored more than 20 publications in top conferences such as KDD, WWW, RecSys, VLDB, SIGIR, CIKM, and SPAA.

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Webinar: Description here

Date & Time: Wednesday, April 22, 2018