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AI is playing a key part in reshaping and developing businesses, and in improving people’s daily lives. Different concepts, tools and technologies that use algorithms—such as blockchain, machine and deep learning, natural language processing, generative AI, etc.—are beginning to show exciting possibilities that will support and optimise human intelligence. If guided by an ethical and responsible approach, this field can offer numerous rewards.

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Algorithmic biases: neural networks are also influenced by hardware

• Researchers have demonstrated that the fairness of AI models is dependent on hardware platforms used for their deployment. Some hardware configurations have been found to introduce demographic biases which are highly problematic, notably for healthcare applications.
• Model compression is proposed as a key solution for deploying neural networks on devices with limited hardware resources, such as AI capable PCs or edge computing devices.
• The adoption of co-design frameworks for hardware and software architectures will play an essential role in the drive to optimise the fairness and performance of AI models. The integration of non-volatile memory (NVM) devices and noise reduction in neuromorphic systems are also promising avenues for future development.
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Multimodal learning / multimodal AI

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Three people are collaborating around a laptop in a modern office environment. One of them, standing, is explaining something to the two seated individuals, who appear attentive. On the table, there is a desktop computer, a tablet, and office supplies. Plants and desks are visible in the background.
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FairDeDup limits social biases in AI models

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A woman stands in a train, holding a phone. She is wearing a beige coat and a blue and brown scarf. The interior of the train is bright, with seats and metal support bars.
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A mathematical model to help AIs anticipate human emotions

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Automated intervention reports for augmented technicians thanks to generative AI

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David Caswell: “All journalists should be trained to use generative AI”

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Health: Jaide aims to reduce diagnostic errors with generative AI

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