“Causality, Digital Twin & AI in IoT”

There is a new awakening in AI & ML that incorporating Causality is essential to move the field forward. This is because while association or correlation-based ML has brought us many low-hanging fruits, it is not sufficient to get us the *valuable* fruits that are yielded from prescribing specific action to achieve specific results! We are seeing a bifurcation in IoT – Visualization IoT and VIRTUALIZATION IoT. While Visualization IoT adds significant value to IoT applications, greater “gross-margin” value-add potential resides in VIRTUALIZATION IoT. VIRTUALIZATION IoT is all about Digital Twins; We know Digital Twin . . . it is a virtual representation of the physical space – an asset or a system on the plant floor, for example – which allows us to study, understand and prescribe actions without disrupting the physical space till we are confident that our manipulation will maximize the positives and minimize the negatives. The most important gain we can achieve is to prescribe actions that will increase throughput, improve quality and minimize cost. I call this end-state “Precision Works”. We address how to incorporate Causality into Digital Twins and efforts to support the IoT ecosystem by creating a non-profit Industry Consortium. Causality is hard to do but without knowing specific cause and effects, we cannot get close to Precision Works. Within IoT, we have the opportunity to leapfrog the “trough of disillusionment” –and propel us forward.
Who is this presentation for?
Business development
Prerequisite knowledge:
Familiarity with digital twin concept
What you'll learn?
How to incorporate "causality" for increasing productivity through PRESCRIPTIVE Analytics.

Dr. PG Madhavan, Technology Advisor, 5G Open Innovation Lab. He is the creator of “What-If” Digital Twin. PG’s career in corporate technology includes developing multiple AI, ML and Causality startups for NEC Corporation and product leadership roles at Microsoft, Bell Labs, Rockwell Automation and GE Aviation. PG founded and was CEO at 2 startups (and CTO at 2 others) leading all aspects of startup life. He has led the development of large-scale IoT+ML products at major corporations (GE Aviation, Rockwell Automation and NEC as well as other software solutions at Microsoft and Lucent) and startups (Syzen Analytics, NEC startups and Global Logic) involving ML algorithms to cloud software development to business operations. After obtaining his Ph.D. in Electrical and Computer Engineering from McMaster University, Canada, and Masters in Biomedical Engineering from IIT, Madras, PG pursued original research in Random Field Theory and Computational Neuroscience as a faculty member at University of Michigan, Ann Arbor, and Waterloo University, Canada, among others. PG’s recent major contribution in Data Science is the creation of “Systems Analytics”, a blend of Systems Theory and Machine Learning (published in 2016) providing a pathway to formally incorporate “dynamics’ into Machine Learning. https://www.linkedin.com/in/pgmad