Date: Thursday, December 05, 2019
Time: 2:00 PM Eastern Standard Time
Duration: 1 Hour
From autonomous vehicles to health care delivery, Artificial Intelligence (AI) is transforming many types of products and services, as well as the operational structures of companies that deliver them. Yet, despite its rapidly-growing adoption, the technology, its capabilities, applications, and limitations are not well understood.
AI scientist and inventor Dr. Alianna J. Maren will clear up many misconceptions about AI, and give technology decision makers and business line leaders a deeper understanding of how best to leverage AI to support their own missions. She will also address what to expect from the next generation of AI systems, the potential areas of greatest profitability for AI applications—and the steps needed to gain maximal advantage.
Overview of Topics:
- The difference between AI and conventional computing
- AI and machine learning (ML) algorithms, and the computing structures that support them
- Using AI to augment inward- and outward-facing digital services
- Using AI to improve existing products—and create new ones
- Using AI as an operational tool to improve the responsiveness, efficiency, and success of corporations, healthcare delivery, and other institutions
- What AI can and can't do, and the limits of today's algorithms
- Where the next breakthroughs in AI are likely to occur—and what they will make possible
In addition to gaining an understanding of AI’s fundamental concepts and strategic importance, attendees will learn how AI can be applied in three different environments: 1) traditional data centers, 2) "cloud" environments, and 3) edge applications.
Alianna J. Maren, Ph.D.
Author and Faculty, Data Science, Northwestern University
Dr. Alianna J. Maren is a serial inventor. Her most recent work focuses on the 2-D Cluster Variation Method (2-D CVM), which has the potential for modeling brain topographies and enabling more brain-like behaviors (such as free association and building correlations between memories) in deep learning architectures. She currently teaches artificial intelligence and deep learning through Northwestern University’s Master of Science in Data Science program, for which she has developed their two core AI courses.
Dr. Maren is the senior author of the Handbook of Neural Computing Applications (1990, Academic) and is developing a new book, Statistical Mechanics, Neural Networks, and Artificial Intelligence, intended to bridge the gap between entry-level AI and the more advanced AI methods. Her two most recent works, published on www.arxiv.org, are monographs that detail the first known set of 2-D CVM computational results and present the derivation of the equations for variational Bayes, extended to systems with Markov blankets.
In her spare time she likes to sleep, and amuse her two cats.