[AllUsers-ISR] 10 Reasons to Attend SiPS 2020

Mon Oct 19 17:16:49 WEST 2020

10 Reasons to Attend SiPS 2020 Click to Register!

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*10 Reasons to Attend SiPS 2020*
*(it's free!)*

Learn at your own pace!
Register today to access conference materials through November 14.

Learn about the latest ultra-low-power processors for running artificial 
intelligence at the edge

Ask questions during
live sessions, and learn from
your fellow attendees

ONE Zoom call per day!
No need to choose between live sessions.

Understand how Intel is merging artificial intelligence and wireless 
networks towards 5G and beyond

Enjoy the conference from anywhere!
(No economy-class airplane seats this year...)

Find employment and internship opportunities with our Official Sponsors

Learn how to evaluate the efficiency of deep neural networks for a wide 
range of applications

PhD Forum on Tuesday:
Bringing together students and industry experts

Learn about employment and internship opportunities with our Official 
Sponsors

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*How to Prepare for SiPS 2020*
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*Step 1: Register for FREE! *
You will receive unique credentials to SiPS 2020 virtual platform in 
your inbox!

Register Now 
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*Step 2: Enjoy On-Demand content...*
All On-Demand content is available immediately with access to the 
virtual platform!

If you have any questions or comments for the On-Demand presenters, use 
the Conversation tab under each video! Authors and Session Chairs will 
be monitoring their page throughout the conference.

*Step 3: Prepare for tomorrow's **LIVE**Zoom session! *
Each session that will occur Live via Zoom will have an orange (or pink) 
button at the top of the presentation page. (Hint: Each day has its own 
Zoom link, but all of the day's sessions are in the same meeting room!)

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*Know someone else who would enjoy SiPS 2020?*
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*They need to register NOW! All sessions will be available on-demand 
until November 14th, but registration is due on October 22nd!

Secure access to the platform using the link below:*

Register for FREE 
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*Meet the SiPS 2020 Plenary Speakers*
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Presenting *LIVE *via Zoom! /Learn more 
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*Luca Benini, ETH Zurich and University of Bologna*
*Parallel Ultra-Low Power Computing for Extreme Edge AI – A RISC-V Open 
Platform Approach
Monday, 4PM Lisbon (GMT+1) *
Edge Artificial Intelligence is the new megatrend, as privacy concerns 
and networks bandwidth/latency bottlenecks prevent cloud offloading of 
sensor analytics functions in many application domains, from autonomous 
driving to advanced prosthetic.  The next wave of “Extreme Edge AI” 
pushes signal processing and machine learning aggressively towards 
sensors and actuators, opening major research and business development 
opportunities.  In this talk I will focus on recent efforts in 
developing an AI-centric Extreme Edge computing platform based on 
open-source, parallel ultra-low power (PULP) RISC-V processors coupled 
with domain-specific accelerators.

*Vivienne Sze, MIT*
*How to Evaluate Efficient Deep Neural Network Approaches*
*Tuesday, 4PM Lisbon (GMT+1)*
Enabling the efficient processing of deep neural networks (DNNs) has 
becoming increasingly important to enable the deployment of DNNs on a 
wide range of platforms, for a wide range of applications.  To address 
this need, there has been a significant amount of work in recent years 
on designing DNN accelerators and developing approaches for efficient 
DNN processing that spans the computer vision, machine learning, and 
hardware/systems architecture communities.  Given the volume of work, it 
would not be feasible to cover them all in a single talk.  Instead, this 
talk will focus on *how* to evaluate these different approaches, which 
include the design of DNN accelerators and DNN models.  It will also 
highlight the key metrics that should be measured and compared and 
present tools that can assist in the evaluation.

*Shilpa Talwar, Intel*
*5G and Intelligent Wireless Systems
Wednesday, 4PM Lisbon (GMT+1)*
Shilpa Talwar is an Intel Fellow and director of wireless 
multi-communication systems in the Intel Labs organization at Intel 
Corporation. She leads a research team in the Wireless Communications 
Laboratory focused on advancements in ultra-dense multi-radio network 
architectures and associated technology innovations. Her research 
interests include multi-radio convergence, interference management, 
mmWave beamforming, and applications of machine learning and artificial 
intelligence (AI) techniques to wireless networks. While at Intel, she 
has contributed to IEEE and 3GPP standard bodies, including 802.16m, 
LTE-advanced, and 5G NR. She is co-editor of book on 5G “Towards 5G: 
Applications, requirements and candidate technologies.” Prior to Intel, 
Shilpa held several senior technical positions in wireless industry 
working on a wide-range of projects, including algorithm design for 
3G/4G & WLAN chips, satellite communications, GPS, and others. Shilpa 
graduated from Stanford University in 1996 with a Ph.D. in Applied 
mathematics and an M.S. in electrical engineering. She is the author of 
70 technical publications and holds 60 patents.

*Questions? *
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