Machine learning

Deepfakes: detection methods struggle to make limited progress

• Easily created and disseminated audio and audio-visual deepfakes, which can be mistaken for real recordings, are undermining confidence in online media.
• New research has highlighted the importance of enhancing current detection systems, which are far from infallible, with continuous learning and multi-modal artificial intelligence.
• Some progress has been made on the development of detectors, but extensive research will be required to make these tools, which are typically tested under laboratory conditions, function reliably under real conditions.
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Generative AI: a growing threat to information systems

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AI agents could further automate certain jobs

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Devoxx France: “AI has ushered in a second revolution in the world of testing”

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WeWaLK, .lumen: AI simplifies mobility for the blind and partially sighted

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Young woman wearing gloves conducts environmental research by a lake. She uses equipment including a laptop and test kits. Trees and water in the background.

Biodiversity in lakes: multimodal AI crunches eADN data to monitor pollution

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Manipulation, mistrust and adoption: paradoxical responses to AI in companies

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