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Artificial intelligence | Go in-depth

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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The image shows a man sitting at a desk, focused on two computer screens in front of him. He has short hair and a well-groomed beard. He is wearing a white shirt with subtle patterns. In the background, there is a green plant that adds a touch of nature to the work environment. Natural light is coming through a window, illuminating the scene.
Data | Go in-depth

Improving the security of information systems with digital twins

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Artificial intelligence | Go in-depth

Generative AI: a growing threat to information systems

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Research | Go in-depth

Leveraging Mobile Phone Data to understand Temporary Migration in Senegal

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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.
Artificial intelligence | Go in-depth

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

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A man in a safety vest reviews documents in front of a row of colorful shipping containers at a port.
Artificial intelligence | Go in-depth

Contraband: AI efficiently detects anomalies in shipping containers

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Research | Go in-depth

“I lost track of time”: how we get caught up in digital applications?

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