Emerging AI Technologies

There is no shortage of opinions on the potential for AI technologies in business. However, the current round of solutions is often viewed as expensive, proprietary, and complex to deploy and manage. When will AI solutions scale industry-wide? Is it possible to measure ROI for automation? How does AI rank against other corporate initiatives? The state of AI technology and its future is spoken here. From the development of neuromorphic chipsets to democratizing deep learning toolsets and from the next wave of machine vision, emotion, gestures, NLG, new algorithms, HPC and quantum computing will all be shared by the industry’s best and brightest.

Thursday, October 24

7:45 am Registration Opens

8:00 Continental Breakfast

8:50 – 12:15 pm Keynote Session

12:15 pm Networking, Coffee & Dessert in the Expo

1:30 pm Opening Remarks

Schubmehl_DavidDavid Schubmehl, Research Director Cognitive/Artificial Intelligent Systems and Content Analytics, IDC

1:35 AI Executive to be Announced

Dell Executive

2:05 Using AI to Synthesize New Data

Jan Kautz, PhD, Vice President of Learning and Perception Research, Nvidia 

AI is now ubiquitously used to analyze data in large variety of fields, from the sciences to healthcare. However, AI can not only be used to analyze data but also to synthesize new data, such as new visual content. In particular, generative adversarial networks (GANs) have been shown to excel at this task. For instance, they can translate images from one domain (e.g., day time) to another domain (e.g., night time), synthesize completely new images, and even learn to detect defects by synthesizing its own training data. 

2:30 PANEL: The Impact of Quantum Science on Artificial Intelligence

As the field of Quantum Science develops, theoretical proposals have shown that building quantum algorithms could improve computational tasks with AI, including machine learning. Quantum computing could perform computations that are more efficient than classical AI algorithms. This panel of researchers discusses the possibilities of addressing traditional computational challenges and likely paths forward in the fundamental advancement of hardware-based machine learning.

Riordan_MichaelModerator: Michael Riordan, Vice President, Entanglement Institute, Inc. and former instructor at Ethics & Emerging Military Technology Graduate Program, U.S. Naval War College

Wood_LarsPanelists: Lars Wood, CEO, Analog Computation Corp 





Joseph Broz, PhD, Vice President Strategy and Applied Sciences Department Head, SRI International, and Executive Director and Governing Board Chairman, Quantum Economic Development Consortium (QED-C) 




Celia Merzbacher, PhD, Associate Director, Quantum Economic Development Consortium (QED-C) 

3:20 Networking Break in the Expo

4:05 Emotional Intelligence and Affective Computing

Havasi_CatherineCatherine Havasi, PhD, Professor at MIT and AI Lead for Agorai 

Affective Computing is computing that relates to, arises from, or deliberately influences emotion or other affective phenomena. Emotion is fundamental to human experience, influencing cognition, perception, and everyday tasks such as learning, communication, and even rational decision-making. However, technologists have largely ignored emotion and created an often-frustrating experience for people, in part because affect has been misunderstood and hard to measure.

4:35 Best of Both Worlds: Blockchain and AI

Speaker to be Announced

The merits of Blockchain and AI can be shown separately. However, when coordinated in a common application platform, the pair of technologies flourish in applications ranging from building and organizing immense databases, to strengthening cybersecurity protocols and performing tasks at scale beyond the human capability. This session examines the use cases and symbiotic attributes of these technologies.

5:05 Session Break

5:35 Networking Reception in the Expo

6:35 Meetup Groups

7:35 Close of Day 2