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GTC ON-DEMAND

Presentation
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Abstract:
There is a clear opportunity for retailers to generate loyalty and increase sales by focusing on the overall customer experience. We'll describe how we are developing solutions to track customer activity and build profiles based on physical store activity to personalize the in-store shopping experience. We'll also describe how GPUs and deep learning are used to create these capabilities ? all while protecting personal information and privacy.
There is a clear opportunity for retailers to generate loyalty and increase sales by focusing on the overall customer experience. We'll describe how we are developing solutions to track customer activity and build profiles based on physical store activity to personalize the in-store shopping experience. We'll also describe how GPUs and deep learning are used to create these capabilities ? all while protecting personal information and privacy.  Back
 
Topics:
Accelerated Data Science, Intelligent Video Analytics, Data Center & Cloud Infrastructure, Consumer Engagement & Personalization, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8144
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Abstract:

We'll explore the evolution of machine learning from expert systems to shallow learners to and deep learners. We look at the types of algorithms and problems which are addressed by each of these areas. Explore what they mean by artificial intelligence and make a case for a new type of machine learning algorithm embodied in adaptive exploratory systems. The talk will then address how those systems would work in the future to include training sets and adaptation to events in real time. It will address the need for uncertainty quantification and talk to the need for better models and estimation techniques need to do truly predictive analytics.

We'll explore the evolution of machine learning from expert systems to shallow learners to and deep learners. We look at the types of algorithms and problems which are addressed by each of these areas. Explore what they mean by artificial intelligence and make a case for a new type of machine learning algorithm embodied in adaptive exploratory systems. The talk will then address how those systems would work in the future to include training sets and adaptation to events in real time. It will address the need for uncertainty quantification and talk to the need for better models and estimation techniques need to do truly predictive analytics.

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Topics:
Federal, Intelligent Machines, IoT & Robotics
Type:
Talk
Event:
GTC Washington D.C.
Year:
2016
Session ID:
DCS16104
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