I currently serve as CEO of MemryX, Inc., an innovative Edge AI startup founded by professors at the University of Michigan in Ann Arbor. Dr Wei Lu is our co-founder and current CTO, and an expert in memories and neuromorphic computing. We plan to enter production in 2023 with the world's best Edge AI solution.
Prior to MemryX, I worked at Qualcomm for 13+ wonderful years, leading a variety of activities including the Snapdragon roadmap, all technologies for application processing, company strategy, competitive analysis, and more. I joined just prior to the first Android smartphone being launched. My most recent role was as SVP/GM helping Qualcomm diversify from smartphones, and leading several growth businesses including AR/VR, AI, PCs, and gaming. I very much enjoyed working with US partners like Facebook, Microsoft and Google in addition to international customers like Vivo, Oppo, Xiaomi, Sony, Samsung, and so many more.
Prior to Qualcomm, I was able to work at Intel for 8+ years in a number of technology, product, and planning roles in different market segments including laptops, desktops and servers. Together we accomplished a # of industry firsts.
During my time at Intel and Qualcomm, I was deeply engaged in shipping substantially more than 1 Billion advanced chips for mobile personal computing devices. I look forward to helping to grow the use of Edge AI in a number of clients as the world continuously becomes both more intelligent and more connected.
Beyond the world of technology, working with smart/dedicated/honest/ethical people is what keeps me enthused to work each day.
LLMs are driving the frontiers in computer performance today. This talk explores the MLPerf LLM benchmark landscape, the unique challenges of building LLM benchmarks for training and inference, and the challenges for submitters.
David co-founded and is the Head of MLPerf for MLCommons, the world leader in building benchmarks for AI. MLCommons is an open engineering consortium with a mission to make AI better for everyone through benchmarks and data. The foundation for MLCommons began with the MLPerf benchmarks in 2018, which rapidly scaled as a set of industry metrics to measure machine learning performance and promote transparency of machine learning techniques. In collaboration with its 125+ members, global technology providers, academics, and researchers, MLCommons is focused on collaborative engineering work that builds tools for the entire AI industry through benchmarks and metrics, public datasets, and measurements for AI Safety. Our software projects are generally available under the Apache 2.0 license and our datasets generally use CC-BY 4.0.
