“Big Data for AI, Cloud, and Autonomous Driving”
Data has evolved dramatically in recent years, in type, volume, and velocity – with its rapid evolution attributed to the widespread digitization of business processes globally. The rise of mobile devices, the proliferation of social platforms, the rapid growth of mobile internet, big data, artificial intelligence, and autonomous driving, all of which created a huge demand for data solutions and led to the emergence and new developments of cloud computing, storage, edge devices, artificial intelligence, autonomous driving and Internet of things applications. In this year’s CAISS Annual Conference, industry and academia leaders will get together to discuss the Data Solutions for AI, Cloud, and Autonomous Driving.
Date: Dec. 12th , 2020 (Saturday)
Time: 1PM – 3:15 PM (PST)
Venue: Virtual Zoom Meeting
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Agenda:
12:45 – 1:00PM: Check in
1:00 – 1:05PM Introduction
1:05 – 1:15PM CAISS Updates and Transition: Dr. Ganping Ju, CAISS President
1:15 – 1:20PM Introduction to new CAISS President-elect: Yong Jiang
1:20 – 1:50PM Keynote Speech – Dr. John Morris, CTO, Seagate, “Opportunities and Challenges in the Growing Datasphere”
1:50 – 2:20PM Keynote Speech – Prof. Kwabena Boahen, Stanford University, “The Future of Computing: 3D Silicon Brains”
2:20 ~ 2:50PM Keynote Speech – Dr. Fan Wang, Vingroup USA, “Road to Autonomous Driving Vehicles”
2:50 ~ 3:15PM Panel Discussion: key note speakers, BOA and special guest
Keynote Speaker:
Dr. John Morris
Senior Vice President and Chief Technology Officer
Seagate Technology
John Morris is responsible for accelerating technology partnerships with Seagate’s customers, and cultivating emerging customers globally. Prior to his current role, Morris was VP for Seagate’s hard drive and SSD product lines. Before that, he served as VP of Design Engineering for Seagate’s enterprise development group, focusing on technical and strategic alignment with enterprise and cloud customers. Since joining the company in 1996, Morris has held a variety of engineering leadership positions and has been a key contributor to many of Seagate’s core technologies. He holds 32 patents, primarily related to hard drive technologies. Morris earned a Ph.D. and M.S. in electrical engineering from Caltech, and a bachelor’s degree in electronic engineering from California Polytechnic State University, San Luis Obispo
Title of Talk: “Opportunities and Challenges in the Growing Datasphere”
Abstract:
Data is proliferating at an exponential rate. New use cases, like autonomous and connected vehicles, are driving a shift in infrastructure.
This massive growth will require significant infrastructure innovation—from the endpoints creating the data, to the edge supporting faster response times, through the core where data and compute services are centralized. Endpoint devices will require domain-specific optimization for autonomy and security. Data movement will be reduced through distributed-computation and optimized for cost and performance. Mass-capacity storage at the core will be underpinned by the next generation of hard drive technology.
We will talk about how Seagate’s innovation addresses the challenges and opportunities across the evolving datasphere.
Keynote Speaker:
Prof. Kwabena Boahen
Stanford University
Kwabena Boahen (M’89, SM’13, F’16) received the B.S. and M.S.E. degrees in electrical and computer engineering from the Johns Hopkins University, Baltimore, MD, both in 1989 and the Ph.D. degree in computation and neural systems from the California Institute of Technology, Pasadena, in 1997. He was on the bioengineering faculty of the University of Pennsylvania from 1997 to 2005, where he held the first Skirkanich Term Junior Chair. He is presently a Professor of Bioengineering at Stanford University, with a joint appointment in Electrical Engineering. He founded Stanford’s Brains in Silicon lab, which develops silicon integrated circuits that emulate the way neurons compute and computational models that link biophysical neuronal mechanisms to cognitive behavior. His research is interdisciplinary, bringing together the seemingly disparate fields of neurobiology and medicine with electronics and computer science. His scholarship is widely recognized, with over ninety publications to his name. These include a cover story in Scientific American featuring his group’s work on a silicon retina and a silicon tectum correctly “wire together” automatically. (May 2005). He has been invited to give over 70 seminars, plenaries, and keynote talks. These include a 2007 TED talk, “A computer that works like the brain”, that has been viewed half-a-million times. He has received several distinguished honors, including a Packard Fellowship for Science and Engineering (1999) and a National Institutes of Health Director’s Pioneer Award (2006). He was elected a fellow of the American Institute for Medical and Biological Engineering (2016) and of the Institute of Electrical and Electronics Engineers (2016). In recognition of his group’s work on Neurogrid (2006-12), an iPad-size platform that emulates the cortex in biophysical detail and at a functional scale. As this combination hitherto required a supercomputer, Neurogrid resurged interest in neuromorphic computing. These students went on to lead the design of IBM’s TrueNorth chip. In his most recent research effort, the Brainstorm Project, he led a multi-university, multi-investigator team to co-design hardware and software that makes neuromorphic computing much easier to apply. A spin-out from his Stanford group, Femtosense Inc (2018), is commercializing this breakthrough.
Title of talk: The Future of Computing: 3D Silicon Brains
Abstract:
AI’s commercial success in the last decade culminates a shift half-a-century ago from developing newfangled transistors to miniaturizing integrated circuits in 2D. With billions of richly interacting mathematically abstracted neurons, deep nets benefited enormously from this paradigm shift. But now communicating a neuron’s output to another’s input uses 1,000× the energy it took to compute it, diminishing the returns of miniaturization and spurring a paradigm-shift from shrinking transistors and wires in 2D to stacking them in 3D. While 3D’s compactness minimizes data movement, surface area drops drastically, severely constraining heat dissipation. Starting from the first-principles, I will show how this thermal constraint may be satisfied by repurposing the neocortex’s unary coding and order sense.
While quantum computers reign supreme in scaling computation by using quantum bits and entanglement with superposition, the cortex reigns supreme in scaling communication by integrating unary (as opposed to deep-nets’ binary) signals in dendrites sensitive to temporal order (as opposed to sum-and-threshold). Realizing its supreme scaling will facilitate a nascent 2D-to-3D paradigm-shift and make it feasible to deploy GPT-3—an AI that can intelligently answer questions based on knowledge assimilated from scouring vast troves of information on the internet—on-device. This new field of temporal computing will disrupt binary computing and substantially accelerate IT’s progress for decades.
Keynote Speaker:
Dr. Fan Wang
Head (Director) of Autonomous Driving R&D Center, Vingroup USA
Dr. Fan Wang is currently the head (Director) of Autonomous Driving R&D Center in Vingroup USA, leading the U.S. and Vietnam teams to develop and deploy the Autonomous driving solution on production vehicles. Before that, Dr. Wang was the director of Autonomous Driving in SF Motors in Santa Clara. His team has been running and testing Autonomous vehicles on California public roads since 2018. Earlier, Dr. Fan Wang holds multiple management and leadership positions in Samsung North America and Qualcomm Inc. Dr. Wang received his B.S in Tsinghua University, Master and Ph.D. in the University of Arizona. He has published dozens of academic papers and coauthored >30 international patents.
Title of Talk: “Road to Autonomous Driving Vehicles”