2018 Artificial Intelligence Panel

From AlphaGo to OpenAI Five, from GPU to TPU, the breakthroughs of Artificial Intelligence has been empowered and accelerated by the advance in high-performance, high-efficiency AI hardwares. AI chips has become the next boom in the AI industry. In AI panel, we invite the brightest minds and experienced expertises from both academia and industry to share their deep insights about the frontiers in AI hardware design and the future of AI industry.


2018 HIGHLIGHT SPEAKERS

 
  Will Knight (Moderator)

Will Knight (Moderator)

Will Knight is the senior editor for AI at MIT Technology Review. I mainly cover machine intelligence, robotics, and automation, but I’m interested in most aspects of computing. Before joining this publication, I worked as the online editor at New Scientist magazine.

 
  Song Han | 韩松

Song Han | 韩松

Song Han is assistant professor at MIT EECS; his lab focuses on Hardware, AI and Neural-nets. Dr. Han received the Ph.D. degree in Electrical Engineering from Stanford advised by Prof. Bill Dally. Dr. Han's research focuses on energy-efficient deep learning. He proposed “Deep Compression” that widely impacted the industry. His work on deep compression and hardware acceleration received the best paper award in ICLR'16 and FPGA'17. Dr. Han's research led to a startup DeePhi Tech that he co-founded. DeePhi provides efficient solutions for deep learning computing. DeePhi has been acquired by Xilinx to make world-wide impact.

 
  Zhangxi Tan

Zhangxi Tan

Zhangxi Tan is the CEO and Co-founder of OURS technology. Tan received PhD in CS from Berkeley and BE in EE from Tsinghua University. He is specialized in computer architecture and VLSI designs, and served as Founding Engineer and also the first chip designer of Pure Storage, a publicly listed company in NYSE. He is also the founding member and lead designer of FlashBladeTM. Tan holds 20+ patents on flash storage and hardware accelerators including one of the few open-source SPARC CPU implementations  (RAMP Gold), and is the winner of 2017 AIconics Best Innovation award in AI Hardware. Their customers include Tesla, Mercedes F1 racing team, Riot Games 

 
  Li Jing | 靖礼

Li Jing | 靖礼

Li Jing is a co-founder of Lightelligence where he leads the AI algorithm team. He is currently a PhD student in MIT Physics Department and conducts research in machine learning and applied physics. Lightelligence is a MIT spin-out company that uses integrate photonics to build AI accelerator. By processing information with light, their chips offer ultra high speed, low latency, and low power consumption for AI applications.