Wei Li, Vice President and General Manager of Machine Learning Performance, Intel 
Why Attend
AI optimization and acceleration so far has mostly been driven by novel hardware innovations. However, recently there have been new products developed by the AI start-up and research communities that operate at the software level in the machine learning technology stack, which reduce training length, inference time, energy consumption and memory usage of AI and machine learning (ML) models.
Learning how to benchmark, deploy, and use these tools, as well as scrutinizing existing real-world use-cases is business-critical because these tools disrupt the AI market by:
- Enhancing the running of ML models on CPUs, therefore, reducing the costs of ownership of AI hardware
- Improving the performance of standard AI accelerators (GPUs, FPGAs, DSPs etc.)
- Helping more data science and machine learning projects get into full production
- Increasing the competitiveness of products in the crowded edge device and IoT markets
The Software for AI Optimization Summit will demonstrate how to deploy and integrate the latest novel software optimization tools into AI/ML workflows. Consequently, innovators and adopters in data science, machine learning, AI engineering and IoT solutions will uncover new techniques that enable the training and inference of AI and ML models to be faster, more cost-efficient, and still maintain high levels of performance and accuracy.
Consequently, you will be ahead of the latest innovations across the ML technology stack enabling you to make informed decisions about strategic partnerships on who to partner with to optimize AI on the cloud and at the edge.
Key Topics for 2021
Benchmark and understand how training and inference time, energy consumption and memory usage of AI is impacted by software for AI optimization
Navigate the market by networking with End-Users from the IoT, Edge & Cloud, AI Hardware Vendors, Researchers, Software Providers & Investors
- Learn from use cases how to deploy models on resource-constrained devices and create space for additional functionality
Hear from practitioners in MLOps on how to get more machine learning and data science projects into production
Collaborate with partners in the AI ecosystem across the software and hardware stack to achieve end-to-end optimization and acceleration
The ML technology stack and the optimizations possible at each level
The Agenda
Download the Software for AI Optimization 2021 agenda.
Watch highlights from the AI Hardware Summit 2019:
Download the agenda
Speakers
Andrew Richards
Wei Li
Wei Li is Vice President and General Manager of Machine Learning Performance at Intel Corporation, where he is responsible for AI software product development for deep learning, statistical machine learning and big data analytics, as well as hardware co-design for AI acceleration on CPU, GPU, and XPU architectures with heterogenous and distributed computing. He is passionate about product technology innovation and his team’s work has been instrumental in realizing Intel's multi-billion dollar AI revenue growth.
As a performance software technologist, he has led teams to win competitions and set performance world records in AI, data analytics and high performance computing. He received his Ph.D. in Computer Science from Cornell University and completed an executive accelerator program at the Stanford Graduate School of Business.
Peter Grabowski
Rashmi Gopinath
Alvin Andrian
Zach Shelby
Zach is an entrepreneur, angel investor and technologist in the embedded space with a passion for TinyML, embedded and Internet engineering. Zach is a former Arm VP, founder and CEO of the Micro:bit Foundation and Sensinode, active in several of his portfolio companies, and is working to bring ML to any embedded device as co-founder and CEO of Edge Impulse.
Prior to this, he served in a number of roles at Arm, including VP of developers, VP of marketing, and director of technology for IoT. Zach was the co-founder and CEO of the Micro:bit Foundation and the co-founder of Sensinode, acquired by Arm in 2013, where he acted as CEO and CTO. He is an active investor and advisor for tech startups, including CubiCasa (PropTech), Augumenta (AR), Petasense (Industrial IoT) and Walkia Lighting (LED lighting). Before starting Sensinode, he led wireless Internet networking research at the Centre for Wireless Communications and at the Technical Research Center of Finland. Zach has served on the Technical Advisory Board and Board of Directors at the IPSO Alliance, has contributed to numerous IoT-related standards and was awarded the Nokia Foundation Award in 2014 for his work on the Internet of Things.
Calin Barburescu
Werner Bailer
Rangan Sreenivas
Dr. Bernd Waschneck
Michael Azoff
With over 17 years analyst experience, most recently at Ovum/ Informa, Michael Azoff joined Kisaco Research, the company behind the AI Hardware and Edge AI Summit series, in 2020 as Chief Analyst.
Eitan Michael Azoff, PhD, MSc, BEng.
HQ’d in Kisaco Research’s London office, Michael's current focus is launching Kisaco Research vendor product comparison reports with the new Kisaco Leadership Chart (KLC) analyst chart. The first KLC is also the first analyst chart in the AI chip industry, with 16 vendors having participated in the research.
In his career Michael worked at Rutherford Appleton Laboratory building simulators for electron and hole transport in semiconductors for UK national and European community research projects and published papers in learned journals. He then turned to building neural networks and created a startup selling his Prognostica Microsoft Excel add-in for time series forecasting, and wrote a book on the topic for publisher John Wiley & Sons in 1994.
Since 2003 Michael has worked as an IT industry analyst covering software engineering topics, from agile and DevOps, to application lifecycle management and cloud native computing. He started covering machine learning when deep learning emerged as the most recent wave of interest in AI and left his position as Distinguished Analyst at Ovum/Informa to join Kisaco Research and help build an analyst capability within the company.
My analyst coverage areas at KR Analysis
My first research project at KR was to create the first analyst comparison chart for AI chips. We invited AI chip producers to participate and were fortunate to have 16 vendors participate from across the globe: USA, UK, France, and China, and a mix of established players (Nvidia, Imagination, Intel, and Xilinx, to startups.
Our analysis showed that the market naturally fell into three areas of hot activity:
▪ Data centers and high-performance computing environments (HPC): here large boxes are installed and the aim is to achieve maximum performance for training and inferencing AI systems. The buyers are cloud hyperscalars, national research labs and agencies, and some large enterprises with big investments in AI.
▪ Small edge: the opposite end of the spectrum, building the smallest useful chip possible to sell as cheap as possible and embed in edge devices. AI is inferencing here.
▪ Automotive: an active industry in AI but highly regulated creating hurdles and technology adoption cadences that can be challenging for suppliers. AI is mainly inferencing here (for systems installed in vehicles).
We produced four Kisaco Leadership Charts out of this research.
We are also researching the machine learning (ML) software tools space, and our first report here is ML Lifecycle Solutions. The biggest challenge for enterprises is taking the research AI systems developed by their data scientist and deploying these into production at scale. Using a host of open source tools to achieve this is possible but time consuming to build and maintain, as well as prone to breakdown. This is why the ML lifecycle solution space exists.
Finally, in our first batch of KR Analysis reports we produced the KLC on engineering application lifecycle management (ALM) solutions. While ALM has been in existence as a distinct practice since KR Analysis and Michael Azoff introduction © Kisaco Research. All rights reserved. Unauthorized reproduction prohibited. 4 around 2003, it continues to evolve. We found the engineering and highly regulated industries relying on engineering and compliance oriented ALM to help manage risk and complexity.
David Kanter
Ranjeet Singh
Yvonne Lutsch
Venkatesh Wadawadagi
Venkatesh is a senior data scientist, practice leader, author and speaker. As a solution consultant at Sahaj Software Solutions, he helps businesses solve complex problems using AI-powered solutions.
He specialises in Deep Learning, Computer Vision, Machine Learning, embedded-AI and business intelligence. He has extensive experience in building algorithms, leading the teams/efforts, architecting the solution and research. He has worked on a variety of solutions ranging from building brand monitoring systems, building a Deep Learning Inference Engine for an e-AI chip, implementing Adaptive Traffic Control System to research and development in the area of ATM surveillance.
He also has experience of working across other areas like Video Codecs, embedded systems, FPGA subsystems and Linux programming & development. Earlier he has worked with the Uncanny Vision Solutions and Pathpartner Technology.
Simon Wiedemann
Peter Buckingham
Nic Lane
Frédéric Desbiens
Who will be there
PORTFOLIO ATTENDEES
Gold Partner
Event Partner
Applied Brain Research
Website: https://appliedbrainresearch.com/
Please visit our website for more information.Media Partners
Edge IR
Website: http://www.edgeir.com
Edge Industry Review (EdgeIR.com) is a news, analysis and industry resource website documenting the changes taking place on the edge of the internet infrastructure market – the present and the future of the Edge Computing ecosystem.
IoT Global Network
Website: http://www.iotglobalnetwork.com
IoT Global Network
Discover the world of IoT.
IoT Global Network is the ultimate intelligence platform for the global machine-to-machine communication value chain.
IoT Global Network serves as an invaluable source of information for IoT decision makers in all areas of industry and public services, including consumer-related, energy, financial, industrial, healthcare, security and transportation, – and anyone else who would like to learn more about how the Internet of Things will shape tomorrow’s society.
Discover. Learn. Connect. Engage.
Tryolabs
Website: http://bit.ly/2s1lRiz
Tryolabs machine learning consulting teams excel at helping companies improve their KPIs by leveraging their own data. They combine computer vision and natural language processing skills, ability to build forecasting models and full-stack development capabilities to craft solutions that can improve revenue streams and reduce operational costs.
Tryolabs also engages and gives back to the community as much as possible. Some of their efforts include open-source projects, machine learning talks and workshops around the globe, meetups, event listings, and a blog.
Become a Sponsor
Kisaco Research provides the much-needed platform on which industry executives can network, connect and learn from each other as well as meet potential industry partners.
Far from the typical ‘meet-and-greet’ exhibition experience, you – as a sponsor or exhibitor – will be positioned as a partner of the event with a focus on the benefits of your product and brand, rather than just a name on an exhibition list.
With our extensive marketing experience and strategy, your partnership with Kisaco Research will grant you a sponsorship package that is an extension and enhancement of your current marketing and branding efforts. We value your ROI and will work with you directly on your specific goals and targets – that’s why we take special care in finding the most relevant end-users to attend, so that your financial and resource investment is smartly allocated.
Find out more by calling us at +44 (0)20 3696 2920 or email us at [email protected].
SOFTWARE FOR AI OPTIMIZATION POSTER PRESENTATION
Looking to showcase your research, use cases, or software to the AI, ML, and data science communities?
Researching, using, or developing software for AI optimization? Our dedicated poster sessions are perfect to get your work noticed by the
AI, ML, and data science communities.
Posters that are displayed will be subject to checks and successful registration. Posters should be a one page PDF in portrait orientation.
Poster abstract submission deadline is 6pm (EST) on Friday May 7, 2021.
If you have any questions please contact [email protected]
Conference Packages
Sending Your Team? Group Discounts Available!
Applicable for Primary Market, Service Provider and Industry Rates Only. Not available for Academic or ‘Start-Up’ rates
Book a Team of 3+ - Save an Additional 10% Off
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If you would like to register a team of 3 or more, please email [email protected] for your discount coupon code before registering. PLEASE NOTE: Discounts cannot be combined with Early Bird Pricing or any other discount or offer. If you have any questions about your registration, please call us on +44 (0)20 3696 2920
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Interested in a media partner pass?
We have a very limited number of press passes available to attend the event. If you regularly cover the AI chip industry and want to stay at the cusp of innovation and hear the latest product and company launches, get in touch.
Contact: Finola McMahon, Marketing Director, [email protected]
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