The RISELab faculty—who cover the fields of machine learning, systems, security, and hardware—have just published a vision paper on systems challenges for AI. They argue that future AI systems must make timely and safe decisions in unpredictable environments, be robust against sophisticated adversaries, and process ever increasing amounts of data across organizations and individuals without compromising confidentiality. These challenges will be exacerbated by the end of the Moore’s Law, which will constrain the amount of data these technologies can store and process. They propose several open research directions in systems, computer architecture, and security that can address these challenges and help unlock AI’s potential to improve lives and society.
Link to the press release: https://news.berkeley.ed