Machine learning

Cybersecurity: AI attacks and hijacking

● AI and generative AI systems can be easily hijacked to generate malicious code, even when designed to reject such requests.
● Other types of attacks, known as "model evasion attacks," exploit modified inputs to cause unexpected behaviours in AIs, such as making a self-driving car misinterpret traffic signs.
● Poisoned data can introduce backdoors into AI models, leading to unintended behaviours, which is concerning due to the lack of control engineers have over their data sources.
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Combining Clustering and AI for Congestion-Free Mobile Networks

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GettyImages - earthquake - séisme

Search and rescue: drones that detect human voices under collapsed buildings

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Voice without vocal cords: a machine learning assisted device that enables patients to speak

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Low-noise innovations: How sounds are contributing to the future of telecoms

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Neurotechnology: auditory neural networks mimic the human brain

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PLEAIS

P-C. Langlais (PLEAIS): “Our language models are trained on open corpora”

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