Teaching machines in the way that animal trainers mold the behavior of dogs or horses has been an important method for developing artificial intelligence and one that was recognized Wednesday with the top computer science award.Teaching machines in the way that animal trainers mold the behavior of dogs or horses has been an important method for developing artificial intelligence and one that was recognized Wednesday with the top computer science award.Computer Sciences[#item_full_content]

Researchers at the Carnegie Mellon University Robotics Institute and the Massachusetts Institute of Technology (MIT), created CHARCHA ( Computer Human Assessment for Recreating Characters with Human Actions), a secure and personalized verification protocol that allows an individual’s likeness to appear in generative video content. The team was inspired to create CHARCHA to respond to ethical issues in generative AI, such as unauthorized deepfakes. The research is published on the arXiv preprint server.Researchers at the Carnegie Mellon University Robotics Institute and the Massachusetts Institute of Technology (MIT), created CHARCHA ( Computer Human Assessment for Recreating Characters with Human Actions), a secure and personalized verification protocol that allows an individual’s likeness to appear in generative video content. The team was inspired to create CHARCHA to respond to ethical issues in generative AI, such as unauthorized deepfakes. The research is published on the arXiv preprint server.Security[#item_full_content]

How do AI-generated ad slogans compare to those created by professionals? New University of Minnesota research suggests that the pros tend to connect better with consumers, but AI tools may perform just as well by adopting certain strategies.How do AI-generated ad slogans compare to those created by professionals? New University of Minnesota research suggests that the pros tend to connect better with consumers, but AI tools may perform just as well by adopting certain strategies.Consumer & Gadgets[#item_full_content]

Nikita Belyakov and Svetlana Illarionova, researchers from the Skoltech AI Center, presented a new method for semantic segmentation of multispectral data, which can be used to recognize clouds, shadows, and snow patches in satellite images. This approach will increase the accuracy of recognizing complex climatic structures in images without additional human involvement in data annotation.Nikita Belyakov and Svetlana Illarionova, researchers from the Skoltech AI Center, presented a new method for semantic segmentation of multispectral data, which can be used to recognize clouds, shadows, and snow patches in satellite images. This approach will increase the accuracy of recognizing complex climatic structures in images without additional human involvement in data annotation.Computer Sciences[#item_full_content]