PANEL: Open panel and discussion on tackling complexity, reproducibility and tech transfer challenges in a rapidly evolving AI/ML/systems research

ABSTRACTDiscussion is centered around the following questions: * How do we facilitate tech transfer between academia and industry in a quickly evolving research landscape? * How do we incentivize companies and academic researchers to release more artifacts and open source projects as portable, customizable and reusable components which can be collaboratively optimized by the community across diverse models, data sets and platforms from the cloud to edge? * How do we ensure reproducible evaluation and fair comparison of diverse AI/ML frameworks, libraries, techniques and tools? * What other workloads (AI, ML, quantum) and exciting research challenges should ReQuEST attempt to solve in its future iterations with the help of the multi-disciplinary community: reducing training time and costs, comparing specialized hardware (TPU/FPGA/DSP), distributing learning across edge devices, ...