AI: Use Cases, Trends and Opportunities

Speaker:               Dr Tok Wee Hyong

                               Principal Data Scientist Manager

                               Microsoft, Washington

----------------------------------------------------------------------------------------------------------------------------------------------------------- 

Date/Time:          29 Nov 2017, Wednesday, 10:00 AM to 12:00 PM

Venue:                  Cerebro, COM1 02-05

Chaired by:          Dr Chan Mun Choon, Associate Professor, School of Computing

                               (chanmc@comp.nus.edu.sg)

 -----------------------------------------------------------------------------------------------------------------------------------------------------------

Abstract:

MIT Technology Review describes “AI is the New Black”, and noted that “Artificial intelligence no longer exists just in the realm of science fiction. Enterprise AI is coming of age and cognitive computing is now actively improving business processes and strategies.”. Organisations are using AI to create intelligent applications and experiences that are more intuitive, more conversational, and simply more intelligent. This has helped companies accelerate their digital transformation at a blazing pace.

Join Wee Hyong in this talk as he shares the latest AI use cases that his team has been working on, and the trends and opportunities in AI. The talk will cover how we can all weave AI experiences into the fabric of everyday things.

 

Biodata:

As Principal Data Science Manager, Wee Hyong Tok leads the Cloud AI Innovation Team at Microsoft, where his team works on cutting-edge AI projects, that continuously push the boundaries of AI. Wee Hyong has worn many hats in his career, including developer, program/product manager, data scientist, researcher, and strategist. Over the years with Microsoft, he has advised many Fortune 500 companies on data platform architectures, and using AI for their strategic initiatives.

 

Wee Hyong is also an affiliate professor with the University of Washington, where he teaches data science courses. He co-authored several books on artificial intelligence – including the first book on “Predictive Analytics Using Azure Machine Learning”, and “Doing Data Science with SQL Server”, and is currently working on an upcoming book on deep learning.