Deep learning

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

• Pollution and land-use change pose a major threat to biodiversity in lakes and other natural ecosystems.
• A team of scientists from the University of Birmingham is pioneering an innovative approach involving explainable machine learning to study these complex dynamics.
• Their research, which highlights hitherto unforeseen environmental impacts, will pave the way for better management of complex ecosystems.
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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.
A man in a safety vest reviews documents in front of a row of colorful shipping containers at a port.

Contraband: AI efficiently detects anomalies in shipping containers

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Artificial intelligence: how psychology can contribute to AGI

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Explainability of artificial intelligence systems: what are the requirements and limits?

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Two people collaborate in front of computer screens, one pointing something out to the other. The screens display computer code in a modern office environment.

AI: “the divide between freelance and in-house developers can be damaging”

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A group of people is attending a presentation of BrainBox AI at the Orange OpenTech event. Two presenter stands in front of a screen displaying graphs and information on the topic. The participants are listening attentively and appear engaged in the discussion.

BrainBox AI to cut commercial real estate emissions by up to 40%

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A group of mining workers is listening to a colleague who is explaining something. They are wearing yellow safety helmets and masks. The environment is dark, with rocky walls visible in the background. The guide is using a headlamp to light his way.

AI fed on data from gas sensors and smart cameras prevents workplace accidents

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