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Regulating deepfakes and generative AI in India | Explained

Regulating deepfakes and generative AI in India | Explained
thehindu.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from thehindu.com Daily Mail and Mail on Sunday newspapers.

Madhya Pradesh , United Kingdom , United States , Sergio Massa , Arvind Kejriwal , Volodymyr Zelenskyy , Zara Patel , Rashmika Mandanna , Javier Milei , Justice Manmohan , Joe Biden , Kamal Nath , Manoj Tiwari , Shehnaz Ahmed , Information Technology Ashwini Vaishnaw On , Delhi Police Special Cell , Information Technology Meity Rajeev Chandrasekhar , Deeptrust Alliance , Cyberspace Administration Of China , Massachusetts Institute Of Technology , Information Technology , European Union , Delhi High Court On , Madhya Pradesh Congress , Digital Services , Vidhi Centre For Legal ,

A guide to spotting AI fakes in 2023

A guide to spotting AI fakes in 2023
dazeddigital.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from dazeddigital.com Daily Mail and Mail on Sunday newspapers.

United Kingdom , Israel General , Openai Sam Altman , Elon Musk , Textthom Waite , Media Lab , Stable Diffusion , Google Search , Detect Fakes ,

RUDN Mathematicians Create Neural Network to Detect Fakes in Social Media

RUDN Mathematicians Create Neural Network to Detect Fakes in Social Media
sciencex.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from sciencex.com Daily Mail and Mail on Sunday newspapers.

Saudi Arabia , Ammar Muthanna , Tahir Ahmad , Scientific Center , Modeling Wireless Networks , Create Neural Network , Detect Fakes , Social Media , Long Short Term Memory Chain Method , Applied Sciences ,

Deepfake detection by human crowds, machines, and machine-informed crowds

The recent emergence of deepfake videos raises theoretical and practical questions. Are humans or the leading machine learning model more capable of detecting algorithmic visual manipulations of videos? How should content moderation systems be designed to detect and flag video-based misinformation? We present data showing that ordinary humans perform in the range of the leading machine learning model on a large set of minimal context videos. While we find that a system integrating human and model predictions is more accurate than either humans or the model alone, we show inaccurate model predictions often lead humans to incorrectly update their responses. Finally, we demonstrate that specialized face processing and the ability to consider context may specially equip humans for deepfake detection.

The datasets and code generated and analyzed during the current study are available in our public GitHub repository, <https://github.com/mattgroh/cognitive-science-detecting-deepfake ....

Alicia Guo , Kim Jong Un , Vladimir Putin , Massachusetts Institute Of Technology Committee , Media Lab , Deepfake Detection Challenge , Detect Fakes , Two Alternative Forced Choice , Single Video Design , Kim Jung Un , Massachusetts Institute , Experimental Subjects , Exempt Category , Benign Behavioral , Deep Fakes , Affective Computing , Human Cooperation ,