Next big thing: Understanding how machine learning actually works
By David Frazier, contributing writer for Cosmosmagazine.com
Many decisions you make in the modern world, and nearly every single action you take, is essentially recorded and, at some point, fed through a model.
Decoding lies with AI? New ML model uses facial expressions and pulse rates to detect deception
By Rachel Schepke, contributing writer for Psypost.org
Researchers from the Tokyo University of Science recently published a study in the journal Artificial Life and Robotics where they explored how machine learning can help detect deception.
Cambridge researchers are developing uncertainty into machine learning systems
By Astha Kumari, contributing writer for Marktechpost.com
In a world of uncertain human insights, embracing uncertainty could help machines and humans work together more effectively and reliably. While current systems are programmed to assume that human interventions are always accurate and confident, this research considers uncertainty in such interactions. A team of researchers from the University of Cambridge has created “ UElic,” a platform to collect real-world human uncertainty data and demonstrate its value in improving models’ ability to handle uncertainty. It emphasizes the significance of allowing humans to express uncertainty in enhancing the reliability of machine learning models.
Combating phishing attacks using AI and machine learning technologies
By Nihad A. Hassan, contributing writer for Cybernews.com
The growth in AI technology and its wide accessibility to the public has added significant power to cyber attackers, who leverage it to craft more convincing phishing messages to victims. But it’s not all bad news – AI technology can be used on the good side, too.
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