AIMS OF THE 2019 SUMMIT
The inaugural AI Hardware Summit sold out in 2018 & is the premier premier event for the AI chip ecosystem.
The 3 core aims of the Summit are:
To assemble the critical mass of the global industry to promote innovation & adoption of silicon & systems for processing deep learning, neural networks & computer vision.To serve as the venue where the technology roadmap of emerging AI hardware is analyzed & updated each year.To connect silicon & systems vendors & hardware innovators to customers, partners, ML researchers & investors.
Take advantage of over 9 hours of dedicated networking time to meet key industry leaders, whilst also exploring:
Luminary Keynotes: Unique perspectives from industry luminaries in hardware (John Hennessy), AI (TBC) & investment (Lip-Bu Tan).
Innovations & Optimizations of Silicon & Systems for AI Training & Inference: Presentations & product launches from C-level executives from AI chip start ups, semiconductor companies & systems OEMs.
Training & Inference at Hyperscale & AI Accelerators in the Data Center Hardware Environment: Deployment & maintenance of AI infrastructure in data centers, hardware requirements for training & inference at scale.
Inference in Client (Edge) Computing: Applications for AI accelerators in cameras, consumer electronics, autonomous vehicles etc.
Beyond Compute: AI's Impact on Memory, Storage & Networking: Innovations in HBM, on-chip memory & NVM, I/O bottlenecks, data transfer & high-speed interconnects.
The Impact of Future ML Models on Hardware Design: Machine Learning co-design, robustness & reprogrammability, model standardization & interoperability.
AI Chip Design & Commercialization: Design, testing & manufacturing, form factors & routes-to-market.
Financial & Industrial Analysis: Market growth & maturity, VC investment trends & dynamics, the commoditization of the inference market, benchmarking & metrics.
Two overarching efforts are indispensable in this AI chip development frenzy: objectively evaluating & comparing different chips (benchmarking), & reliably projecting the growth paths of AI chips (road mapping).
White Paper on AI Chip Technologies: Tsing Hua University & Beijing Innovation Center for Future Chips, December 2018.
WHAT'S DIFFERENT TO 2018?
4 hours extra networking time.
Improved representation from AI hardware value chain.
Whole second floor of Computer History Museum.
All presentations to be made available to registered attendees on day 1 of the conference.
15+ extra speakers.
10+ extra partners.
Deep dive workshop sessions.
Improved on-site experience (branding, catering, networking).