Manual Effort
Research on "manual effort" in various scientific domains focuses on minimizing or replacing human labor through automation and AI. Current efforts involve developing algorithms and models, such as generative adversarial networks and diffusion models, for tasks ranging from optimizing resource allocation in software development to generating novel designs in engineering. This research is significant because it addresses efficiency and cost reduction across diverse fields, from industrial processes to scientific discovery, while also exploring the ethical implications of AI-driven automation.
Papers
Is it worth the effort? Understanding and contextualizing physical metrics in soccer
Sergio Llana, Borja Burriel, Pau Madrero, Javier Fernández
Self-supervised learning -- A way to minimize time and effort for precision agriculture?
Michael L. Marszalek, Bertrand Le Saux, Pierre-Philippe Mathieu, Artur Nowakowski, Daniel Springer