Worldwide, there are over 100 different hardware accelerators in development for processing machine learning workloads, in both server and client computing environments. Estimates for global market opportunity for AI chips vary between USD 43 billion and USD 91 billion by 2025. In 2018, Intel Corporation claimed data center AI chip revenues of over USD 1 billion, while AI chip start-ups collectively have raised in excess of USD 2.5 billion in funding since 2017. Over thirty companies developing AI processors are based in the APAC region.
“Two overarching efforts are indispensable in this AI chip development frenzy: objectively evaluating and comparing different chips (benchmarking), and 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.
The AI Hardware Asia Summit, aims to introduce the US and Chinese markets to help build a clear roadmap of the global AI chip industry and assess emerging technologies for processing machine learning in the data center and at the Edge.
Presenting Chinese companies include Alibaba, Baidu and Horizon Robotics, while international representatives include Graphcore, Groq, SambaNova Systems and Flex Logix. The event has a high contingent of C-level attendees and is intended for a strategic, decision-making audience.
The agenda includes presentations from:
- Lingjie Xu, Alibaba Inc. on The Long March of AI Chips: Challenges and Opportunities
- Dr Kai Yu, Horizon Robotics on China’s First Commercial AI Vision Processor: A Full-Stack Solution for AI
- Zhang Li, Canaan Creative on Applications of Canaan Creative’s Kendryte K210 AI Chip
- Thomas Andersen, Synopsys on Enabling the Path to Device Intelligence
- Yi Shan, DeePhi (Xilinx) on FPGA-based AI platform, technology, application, and ecosystem’
- Cheng Wang, Flex Logix on A Modular, Scalable Edge Inference Architecture for 1 to >100 TOPS with Very Low DRAM Bandwidth
- Ouyang Jian, Baidu on Baidu Kunlun: Making Computing More Intelligent
- Embedding AI in Everything: Reconfigurable
- Shouyi Yin, Tsing Hua University on Architecture for Energy Efficient Neural Network Processing
- Kunle Olukotun, SambaNova Systems on Designing Computer Systems for Software 2.0
All speakers will be available to meet with potential customers, partners and industry peers.
To download the full agenda visit www.aihardwaresummit.com.
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