Jim Keller to Keynote AI Hardware & Edge AI Summit
March 16, 2023 -- Jim Keller, chip architect and CEO of Tenstorrent, will present the Hardware Luminary Keynote at this year's AI Hardware & Edge AI Summit, September 12-14, 2023, in Santa Clara, California.
Keller is responsible for the AMD K8 architecture, the Apple A4/A5 processors and many other pioneering chip architectures, and has served in Engineering leadership roles at AMD, Broadcom, Apple, Tesla and Intel, among others. He now leads Tenstorrent, a company that accelerates AI via their Grayskull PCIe Gen4 platform, and via an AI cloud service called AICloud. Tenstorrent have also developed a high-performance RISC-V processor for the AI & server markets.
As the trend of larger and larger models continues to accelerate, better methods and technology across the stack are needed to improve efficiency and reduce cost. Andrew Ng's luminary keynote will focus on how to start with the right data, while Keller's will look at how to start with the right infrastructure.
With several hundred attendees already signed up for this September's event, now is the time to secure a place at the best possible rate. Click here to register.
AI Hardware & Edge AI Summit
The combined AI Hardware & Edge AI Summit now 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.
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.
New at the Summit for 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.
For more information on this year's Summit, visit the website.
Source: AI Hardware & Edge AI Summit
