Why Attend
The combined AI Hardware & Edge AI Summit comprehensively covers the design and deployment of ML hardware and software infrastructure across the cloud-edge continuum.
For Enterprise ML Experts: Attend a unique AI systems event that will give you both hardware and software tools and techniques for training, deploying, and serving machine learning – the program contains a mixture of state-of-the-art topics and practical tutorials, so you know what is out there, and what you can use. 40% of our audience are enterprise ML practitioners just like you!
For Technology Vendors: Attend the premier event for the AI infrastructure ecosystem, which blends systems, software, tooling, and applications for a unique proposition that focuses on making ML faster, more efficient, and more affordable. If your product fits into this category, your peers and customers are here!
New in 2023:
- A whole day dedicated to case studies from cloud to edge including: generative AI, simulation & digital twins, computer vision, NLP, automotive AI, TinyML, and extreme edge.
- Coverage of MLOps, software tools, and ML software infrastructure + discussion of novel training methods including federated & distributed learning, active learning, and multimodal learning.
- Product launches, demos, and showcases on the expanded exhibition floor.
Previous Featured Speakers
Andrew Ng
Dr. Andrew Ng is a globally recognized leader in AI (Artificial Intelligence). He is Founder of DeepLearning.AI, Founder & CEO of Landing AI, General Partner at AI Fund, Chairman & Co-Founder of Coursera and an Adjunct Professor at Stanford University’s Computer Science Department.
In 2011, he led the development of Stanford University's main MOOC (Massive Open Online Courses) platform and taught an online Machine Learning course that was offered to over 100,000 students leading to the founding of Coursera where he is currently Chairman and Co-founder.
Previously, he was Chief Scientist at Baidu, where he led the company’s ~1300 person AI Group and was responsible for driving the company’s global AI strategy and infrastructure. He was also the founding lead of the Google Brain team.
As a pioneer in machine learning and online education, Dr. Ng has changed countless lives through his work in AI, and has authored or co-authored over 200 research papers in machine learning, robotics and related fields. In 2013, he was named to the Time 100 list of the most influential persons in the world. He holds degrees from Carnegie Mellon University, MIT and the University of California, Berkeley.
Jim Keller
Jim Keller is the CEO of Tenstorrent and a veteran hardware engineer. Prior to joining Tenstorrent, he served two years as Senior Vice President of Intel's Silicon Engineering Group. He has held roles as Tesla's Vice President of Autopilot and Low Voltage Hardware, Corporate Vice President and Chief Cores Architect at AMD, and Vice President of Engineering and Chief Architect at P.A. Semi, which was acquired by Apple Inc. Jim has led multiple successful silicon designs over the decades, from the DEC Alpha processors, to AMD K7/K8/K12, HyperTransport and the AMD Zen family, the Apple A4/A5 processors, and Tesla's self-driving car chip.
Alexis Black Bjorlin
Dr. Alexis Black Bjorlin is VP, Infrastructure Hardware Engineering at Meta. She also serves on the board of directors at Digital Realty and Celestial AI. Prior to Meta, Dr. Bjorlin was Senior Vice President and General Manager of Broadcom’s Optical Systems Division and previously Corporate Vice President of the Data Center Group and General Manager of the Connectivity Group at Intel. Prior to Intel, she spent eight years as President of Source Photonics, where she also served on the board of directors. She earned a B.S. in Materials Science and Engineering from Massachusetts Institute of Technology and a Ph.D. in Materials Science from the University of California at Santa Barbara.
Amin Vahdat
Amin Vahdat is a Fellow and Vice President of Engineering at Google, where his team is responsible for delivering industry-best Machine Learning software and hardware that serves all of Google and the world, now and in the future, and Artificial Intelligence technologies that solve customers’ most pressing business challenges. He previously led the Systems and Services Infrastructure organization from 2021 until the present, and the Systems Infrastructure organization from 2019 - 2021. Until 2019, he was the area Technical Lead for the Networking organization at Google, responsible for Google's technical infrastructure roadmap in collaboration with the Compute, Storage, and Hardware organizations.
Before joining Google, Amin was the Science Applications International Corporation (SAIC) Professor of Computer Science and Engineering at UC San Diego (UCSD) and the Director of UCSD’s Center for Networked Systems. He received his doctorate from the University of California Berkeley in computer science, and is a member of the National Academy of Engineering (NAE) and an Association for Computing Machinery (ACM) Fellow.
Amin has been recognized with a number of awards, including the National Science Foundation (NSF) CAREER award, the UC Berkeley Distinguished EECS Alumni Award, the Alfred P. Sloan Fellowship, the Association for Computing Machinery's SIGCOMM Networking Systems Award, and the Duke University David and Janet Vaughn Teaching Award. Most recently, Amin was awarded the SIGCOMM lifetime achievement award for his contributions to data center and wide area networks.
Bratin Saha
Dr. Bratin Saha is the Vice President of Machine Learning and AI services at AWS where he leads all the ML and AI services and helped build one of the fastest growing businesses in AWS history. He is an alumnus of Harvard Business School (General Management Program), Yale University (PhD Computer Science), and Indian Institute of Technology (BS Computer Science). He has more than 70 patents granted (with another 50+ pending) and more than 30 papers in conferences/journals. Prior to Amazon he worked at Nvidia and Intel leading different product groups spanning imaging, analytics, media processing, high performance computing, machine learning, and software infrastructure.
Marc Tremblay
Marc is a Distinguished Engineer and VP in the Office of the CTO (OCTO) at Microsoft. His current role is to drive the strategic and technical direction of the company on silicon and hardware systems from a cross-divisional standpoint. This includes Artificial Intelligence, from supercomputer to client devices to Xbox, etc., and general-purpose computing. Throughout his career, Marc has demonstrated a passion for translating high-level application requirements into optimizations up and down the stack, all the way to silicon. AI has been his focus for the past several years, but his interests also encompass accelerators for the cloud, scale-out systems, and process technology. He has given multiple keynotes on AI Hardware, published many papers on throughput computing, multi-cores, multithreading, transactional memory, speculative multi-threading, Java computing, etc. and he is an inventor of over 300 patents on those topics.
Prior to Microsoft, Marc was the CTO of Microelectronics at Sun Microsystems. As a Sun Fellow and SVP, he was responsible for the technical leadership of 1200 engineers. Throughout his career, he has started, architected, led, defined and shipped a variety of microprocessors such as superscalar RISC processors (UltraSPARC I/II), bytecode engines (picoJava), VLIW, media and Java-focused (MAJC), and the first processor to implement speculative multithreading and transactional memory (ROCK – first silicon). He received his M.S. and Ph.D. degrees in Computer Sciences from UCLA and his Physics Engineering degree from Laval University in Canada. Marc is on the board of directors of QuantalRF.
Previous Industry Verticals Represented Include...
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Pharma & HealthcareGilead Sciences, GSK, Optum Technology, Roche Sequencing Solutions, Siemens Healthcare
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Devices (Medical & Consumer)Axis Communications, Bosch, Jabra, Playstation, Stryker
