Founder & President, AI Technologies
Chair, Future of AI Hardware Track
Welcome everyone to the 2020 ValleyML AI Hardware Conference series, Future of AI Hardware Track
There is no doubt that the impact of Artificial Intelligence in our lives will be more profound and significant than anytime in the past history. AI will transform industries in a similar way that electricity and internet have reshaped our lives.
Hardware is the underlying technology that enables the AI revolution we are experiencing today. The AI workloads use high dimensional deep learning algorithms which require intensive compute power not available by the mainstream general-purpose CPUs. However, parallel processing hardware would work well with deep learning algorithms. While the re-purposed Graphics Processing Units (GPUs) empower the AI workloads in data centers today, there have been several efforts in industry to come up with more efficient customized hardware for deep learning.
The Future of AI Hardware Track will explore the future trends for AI Infrastructure. The week starts with the keynote by Dr. Bill Dally, SVP of Nvidia, who gives his perspective on the future of Intelligence from the current player in the market, followed by talks from PixelDisplay and Hitachi. Later on Tuesday, Dr. Franco Maloberti gives a different perspective on Analog Computing for AI followed by Lip-Bu Tan, CEO of Cadence, giving a keynote on future trends in AI entrepreneurship before a panel discussion of Venture Capitalists (VCs) from Khosla Ventures, Lux Capital, and Cognite Ventures. The week continues with AI startups pitch panel with VCs for early- and late-stage startups.
Please join us in this exciting program to learn more about future trends in AI Hardware. Feel free to get involved and ask questions in the sessions and inspire others, network with peers, and let us know your comments and suggestions.
Sharif Zadeh, Future of AI Hardware Track Chair
M. Sharif Zadeh is a technology entrepreneur in Silicon Valley, Founder and President of AI Technologies, specialized in Artificial Intelligence and Machine Learning (AI/ML), Computer Vision,
Communication Systems, Internet Networks, as well as Business Development for teams and products, with Strong Leadership and Technology Management Experience.
Trained in academia at Stanford, University of California, Berkeley and Davis, and Sharif University of Technology (SUT) in Electrical Engineering and Computer Science, Sharif has extensive industry experience with proven track record for generating meaningful Intellectual Property (IP) through publications at top-tier IEEE Conferences/Journals as well as patents.
Sharif has served as chair and executive board member at IEEE Silicon Valley, Computer Society, SSCS Society, Silicon Valley Engineering Council (SVEC), program chair of IEEE Artificial Intelligence Symposium, Entrepreneurship for AI Ventures and Venture Capitalists panels at Artificial Intelligence Conferences. He also serves as advisor and mentor for Startups in Silicon Valley and for entrepreneurship graduate courses at Stanford University.
Sharif can be reached on LinkedIn: