Google research scientist Pete Florence discusses how robotics can benefit from dense visual representations, neural radiance fields, and large language models....The Gradient From ACM Opinion | January 5, 2023
AI researchers are warning developers to focus more on how and why a system produces certain results than the fact that the system can accurately and rapidly produce...Vice From ACM Opinion | November 2, 2022
To realize the promised benefits of applying AI and ML models at scale, a roadmap of the challenges and potential solutions to sociotechnical transferability is...Nature Machine Intelligence From ACM Opinion | October 24, 2022
Andy Dang, head of Engineering at WhyLabs, discusses observability and data ops for AI/ML applications and how that differs from traditional observability.
Software Engineering Radio From ACM Opinion | October 21, 2022
An interview with Christopher Manning, director of the Stanford University AI Lab and an associate director of Stanford's Human-Centered Artificial Intelligence...The Gradient From ACM Opinion | September 9, 2022