Why Attend
A 2020 report by Frost & Sullivan stated that 90% of industrial enterprises will be utilising edge computing by 2022. The value of the data that can be gleaned from intelligence ‘in the field’ is clear, but the current limitations of low power, on-device compute, data management and processing across the edge computing landscape continue to pose multiple engineering challenges.
We were thrilled with the success of the 3rd annual Edge AI Summit, which was the first ever dedicated summit focused on deploying machine learning on devices, and on the network infrastructure that supports the intelligent IoT. This year is all about Edge AI case studies!
From ultra-low-power microwatt applications at the ‘sensor edge’, to larger milliwatt examples at the ‘device edge’ up to the non-power constrained ‘server-network edge’; we’ll be gathering a global audience (virtually!) to explore the most innovative real-world use cases of hardware and software facilitating AI at the Edge with examples from Uber AI, Google, Bosch, Magic Leap, Rakuten and many more…
The Virtual Experience
Top 10 benefits
- Tailor Your Agenda
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- Improved Audience Visibility
- On-Demand Content
- High Quality Speakers
- More Networking Opportunities
- Save Time & Money
- Increased Content
- More insights
- Business Development Opportunities - Talk to our team to find out out more [email protected].
Platform Preview
Who Will Be There
Hardware & Architectures
Hardware Engineers & Architects – IP, IC Design, Architecture & Engineering, Storage, Memory & Interconnect
Systems & Algorithms
Systems Engineers & Architects, Machine Learning & Algorithm Engineers & Architects, Scientists & Researchers – OEMs, Systems Integrators, CSPs
Software & Applications
Software & Application Developers – Enterprise, IoT, Automotive, Robotics etc.
Infrastructure & Networking
Engineers & Architects, Researchers, Partnerships & Ecosystem Development - Telco Operators, Edge Infrastructure, Connectivity
2020 Sample Attendees Include
2020 Speakers
Alex Sebatier
Anand Joshi
Bryton Shang
Bryton Shang is the founder and CEO of Aquabyte, a Silicon Valley and Norway-based venture-backed company applying machine learning and computer vision to aquaculture fish farming for biomass estimation, sea lice counting, and feed optimization and formulation. Bryton was named to the 2019 Forbes 30 Under 30 in Manufacturing & Industry.
Graduating at the top of his engineering class at Princeton University, Bryton has led several venture-backed startups. Bryton built deep learning algorithms to diagnose cancer as CTO of HistoWiz, a biotechnology firm. He also co-founded iQ License, a brand licensing platform, and Nikao Investments, an algorithmic trading firm.
Chandra Khatri
Chandra Khatri is the Chief Scientist and Head of AI at Got It AI, wherein, his team is transforming the Conversational AI space by leveraging state-of-the-art technologies in order to deliver Self-Discovering, Self-Training, and Self-Optimizing products. Under his leadership, Got It AI is driving the Conversational AI ecosystem towards automation. Prior to Got-It, Chandra was leading various kinds of applied research at Uber AI such as Conversational AI, Multi-modal AI, and Recommendation Systems.
Prior to Uber AI, he was leading R&D for the Alexa Prize Competition at Amazon, wherein he got the opportunity to significantly advance the field of Conversational AI, particularly Open-domain Dialog Systems, which is considered as the holy-grail of Conversational AI and is one of the open-ended problems in AI. Prior to Alexa AI, he was driving NLP, Deep Learning, and Recommendation Systems related Applied Research at eBay. He graduated from Georgia Tech with a specialization in Deep Learning in 2015 and holds an undergraduate degree from BITS Pilani, India.
His current areas of research include Artificial and General Intelligence, Reinforcement Learning, Language Understanding, Conversational AI, Multi-modal and Human-agent Interactions, and Introducing Common Sense within Artificial Agents.
Chris Knorowski
Cheng Wang
CHENG WANG. Senior VP Engineering: Architecture, Software, Silicon. Originally from Shanghai, PRC. BSEECS, UC Berkeley. Cheng has led the architecture, silicon implementation and software development for eFPGA over two generations from 180nm-16nm and now neural inferencing. Two years as VLSI designer at Zoran. MSEE, EE PhD UCLA: designed 5 FPGA chips from 90nm to 40nm. 2013 Distinguished PhD Dissertation Award. 2014 ISSCC Lewis Winner Award for Outstanding Paper. Multiple patents at UCLA and Flex Logix.
Flex Logix’s NMAX platform excels at getting high hardware utilization at batch=1, which is critical for edge applications. Most of the new information is in the 2nd half of the slide deck.
NMAX delivers from 1 to 100+TOPS, as you need, at 10x lower cost and 3-5x lower power than existing solutions because we get 50-80% MAC utilization on tough models, meaning we need less silicon area, and we achieve it with 10x less DRAM bandwidth, meaning less DRAM cost and system power.
Eileen Tanghal
Jason Knight
Marcellino Gemelli
Sumeet Kumar
Dr. Sumeet Kumar is CEO of Innatera Nanosystems, the pioneering Dutch neuromorphic processor company. Dr. Kumar holds an MSc and PhD in Microelectronics from the Delft University of Technology, The Netherlands. He was previously with Intel, where he worked with the Imaging and Camera Technologies Group developing domain-specific tools for the development of complex media processor architectures. At Delft, Dr. Kumar is credited with creating two highly-successful European R&D programmes developing energy-efficient compute hardware for highly automated vehicles, together with organizations including Infineon, NXP, and BMW, among others. He was also responsible for leading industry-focused research on power-efficient multiprocessors and computational neuroscience.
Petro Bigioi
Petronel Bigioi is CTO, Product Licensing of Xperi Corporation. In this role, he leads an experienced engineering team developing image processing and sound solutions to address various problems in the digital still camera, mobile phone, home, automotive and other related markets. XPERI’s imaging and sound technology can be found in more than 5 billion devices worldwide.
Petronel has more than 250 granted and published U.S. and international patents to date. Petronel is an IEEE fellow with over 20 years of experience in the digital still camera and mobile phone industries, working in both signal processing and connectivity. A co-founder of several successful companies (including FotoNation), he is also a pioneer of digital camera connectivity, a co-author and actively involved in the picture transfer protocol (PTP) and PTP-over-IP networks communication standards.
Married, father of four, Petronel enjoys photography, playing ping pong and is a music aficionado in his spare time.
Petronel got his B.Sc. in electronics engineering (1997) from Transilvania University, Brasov. Petronel also holds a couple of master degrees in ASIC design (Transilvania University, Brasov, 1998) and Networks and Communications (National University of Ireland, Galway, 2000). Petronel obtained his Ph.D. in electronics from Transilvania University (2005), his work being recognized by Romanian academy of science with a “Gheorghe Cartianu” award.
Sami Badri
Vera Serdiukova
Vijay Janapa Reddi
Aaron Allsbrook
Ajay Nair
Ajay is an accomplished professional with several years of experience in Hardware and Software industries.
He leads teams in Product Marketing, Product Management, Product & Corporate Strategy, M&A, Engineering and Supply chain functions.
Prior to Google, he was Director of Marketing & Product Management at Broadcom, and has held management roles at LSI Corporation and Synopsys.
Alexander Samuelsson
Amit Goel
Ashwin Swaminathan
Martin Croome
Mike Henry
Ravi Kokku
Roeland Nusselder
Rashmi Gopinath
Magnus Gerward
Marc Julien
Chritos Kolias
Albert Wang
Yvonne Lutsch
Stephane Chevobbe
Sastry Malladi
Anshul Bhatt
Davis Sawyer
Mahesh Makhijani
Rima Raouda
Partners
Gold Partner
Flex Logix
Website: http://www.flex-logix.com
Flex Logix’ NMAX inferencing accelerators provide very high throughput and hardware utilization even at batch size = 1, with low system cost and system power.
NMAX MAC utilization is over 50% even at batch size = 1. For most inferencing engines utilization drops dramatically from batch 10 to batch 1 because they stall loading weights. High MAC utilization means less silicon area needed for the same throughput.
NMAX uses proprietary Flex Logix interconnect technology to utilize local, distributed SRAM very efficiently generating very high local bandwidth and dropping DRAM bandwidth requires to that of 1 or 2 LPDDR4 DRAMs, even for YOLOv3 at 30 frames/second. This lowers power and lowers cost.
NMAX will be available in TSMC16FFC/12FFC in mid 2019.
Event Partner
Mythic
Website: http://www.mythic-ai.com
BRINGING NEXT-LEVEL AI TO EVERY DEVICE CONSTANT EVOLUTION
Mythic envisions a world where every device is intelligent, with human-like senses and high-level understanding of the environment around it. To realize this we built a team of top talent who bring decades of industry experience from across the entire computing spectrum – empowering everyone to challenge assumptions and eliminate the barriers to achieving our mission. They’ve gone beyond conventional digital architectures, memory, and calculation elements – rethinking everything from the ground up: from transistors and physics, through circuits and systems, up to software and AI algorithms. The result: Powerful life-enhancing AI that customers can push into anything – from fitness bands and hearing aids to self-driving cars and robotic drones.
2019 HIGHLIGHTS
2020 Agenda
We are still working on our agenda for the 2021 event. Whilst we work on getting this to you, please complete your details to receive a copy of the Edge AI Summit 2020 agenda to explore the type of topics that will be covered.
Watch highlights from the Edge AI Summit 2019:
Download the Agenda
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