The advent of big data, distributed computing, and machine learning has led us into a new world of artificial intelligence (AI). The concept of AI isn’t new since it’s a theme that’s been frequently dramatized by the entertainment industry. But this fantasized understanding of AI won’t actually help business leverage its full potential. Instead, it creates the fear of “when will AI and robots replace us?” How can we understand AI in a more realistic and practical way that enables business applications? In this talk, Dr. Michael Wu will address this question by looking at the historical development of analytics to understand what AI really entails.
AI is a powerful disruptor and its potential is only limited by our imagination. However, businesses must change and adapt to the disruption it creates before they can realize its benefits. Dr. Wu's talk includes discussion of the importance of digital transformation (DX), which must happen before business can leverage the full potential of AI. Although business culture transformation, such as DX, is always a slow and challenging process, this talk will explore what companies must focus on initially to pave the road for future success. Only then can we move into the bright future of AI.
Dr. Michael Wu is the Chief Scientist at Lithium, where he focuses on developing predictive and prescriptive algorithms to extract insights from social big data. His research spans many areas, including customer experience, CRM, online influence, gamification, digital transformation, AI, etc. His R&D won him the recognition as an Influential Leader by CRM Magazine along with Mark Zuckerberg and other industry giants.
Michael has served as a DOE fellow at the Los Alamos National Lab conducting research in face recognition and was awarded 4 years of full fellowship under the Computational Science Graduate Fellowship. Prior to industry, Michael received his triple major undergraduate degree in Applied Math,Physics, and Molecular & Cell Biology; and his Ph.D. from UC Berkeley’s Biophysics program, where he uses machine learning to model visual processing within the human brain.
Michael believes in knowledge dissemination, and speaks internationally at universities, conferences, and enterprises. His experiences and insights have inspired many global enterprises and are made accessible through “The Science of Social” and “The Science of Social 2”—two easy-reading e-books.
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