IEEE CS Chapter Open House – Everything you need to know about AI & Machine Learning, but were afraid to ask
Monday, September 23, 2019, 4:00PM – 8:30 PM PDT. The event is FREE.
Warm delicious food (no pizza or sandwiches) & drinks will be provided

This Open House event is organized by:
IEEE Computer Society (CS) chapter of Silicon Valley https://computer.ieeesiliconvalley.org/  in benefit of all its members.

Speaker #1: Rohit Sharma
Title: Founder, AI Tech Systems
Topic #1: Machine Intelligence in Design Automation

Speaker #2: Sumit Gupta
Title: VP, AI, Machine Learning, and HPC in the IBM Cognitive Systems business
Topic #2: AI and Machine Learning

Speaker #3: Eric Saund
Title: Research Scientist
Topic #3: Cognitive Architecture in Models for Natural and Artificial Intelligence

Location: SEMI at 673 South Milpitas Boulevard Milpitas, CA 95035-5446 (View Map)

                                                   (Register here)

PROGRAM:
4:00PM – 4:45PM–Registration, Food, Drink, Networking
4:45 – 5:15PM — IEEE CS chapter presentation
5:15PM – 6:00PM — Machine Intelligence in Design Automation
6:00PM – 6:45PM — Dinner and Networking
6:45PM – 7:30PM– AI and Machine Learning
7:30PM – 8:15PM –Cognitive Architecture in Models for Natural and Artificial Intelligence
8:15PM – 8:30PM — Q&A and Adjourn

Speaker #1:
Abstract:
Motivation behind this talk is to throw some light on use of machine intelligence in design automation; a topic that is largely absent from the media and academia. Machine Intelligence is advancing at a rapid pace and claim to this fame is that it is bound to enable an unprecedent degree of automation in every walk of life. Design automation, a field that has been automating semiconductor design for decades, continues to struggle successful applications of Machine Learning

Bio:

Rohit Sharma is an engineer, author and entrepreneur. He has published many papers in
international conferences and journals. He has contributed to electronic design automation
domain for over 20 years learning, improvising and designing solutions. He is passionate about many technical topics including machine learning, deep learning, VLSI characterization, analysis, and modeling. It led him to design and architect several design automation products. He wrote a book on Machine Intelligence in Design Automation in 2018. He has been disseminating information on the use of machine intelligence in design automation since 2017 with his book, blogs, opens source code, contests, webinar, symposium, and other collateral. He currently works for AI Technology and Systems (www.ai-techsystems.com).

2) Speaker #2:
Abstract:
Most of us don’t realize how pervasive AI is in our everyday lives. Facebook recently reported that 200 trillion AI predictions run on their platforms every day. In this talk, we will start by explaining what the various AI terms are, demonstrate what is possible with modern AI methods that was not possible before, and then talk about AI use cases that range from sports, to gaming, to industrial & enterprise.

Bio:

Sumit Gupta is VP, AI, Machine Learning, and HPC in the IBM Cognitive Systems business. Sumit leads the business strategy and software and hardware products for machine learning, deep learning, & HPC, including Watson ML Accelerator (formerly PowerAI) and Spectrum Compute. Prior to IBM, Sumit was the general manager of the AI & GPU accelerated data center business at NVIDIA and was central in building that business from the ground-up to what is now a multi-billion dollars business for NVIDIA. Sumit has a Ph.D. in CS from UC, Irvine, and a BS in EE from IIT Delhi

3) Speaker #3:
Abstract:
*Cognitive Architecture* is a key organizing framework for AI and Machine Learning as well as for understanding natural intelligence. Narrow applied AI and ML can afford to neglect the concept; AGI (Artificial General Intelligence) cannot. This talk will relay major motivations, concepts, and challenges for Cognitive Architectures as exemplified by SOAR and Copycat. At base is the perception/action loop. For conversational agents, the architectural elements of this loop display progress and limitations that explain why we are simultaneously delighted and disappointed by their capabilities.

Bio:

Eric Saund is a research scientist, developer, and consultant whose work spans multiple fields of intelligent systems, including conversational agents, document analytics, perceptually supported user interfaces, machine learning, and computational vision. Eric received a B.S. from Caltech and a Ph.D. in Cognitive Science from MIT. He served in research and research management roles at the Xerox Palo Alto Research Center, he has published widely, his prototypes have served thousands of users, and he has been awarded over 50 patents to date.

Open to all to attend
(Online registration is needed. If you did not register, seating is not guaranteed.)

Call for volunteers for this event:
If you are interested in volunteering at our IEEE CS chapter Open House email us Here.