Research

IoT: new energy-efficient chips could expand the scope of artificial intelligence in edge computing

• The excessive power consumption of GPUs in artificial intelligence applications has encouraged researchers to develop a novel chip architecture that could pave the way for the widespread adoption of edge AI.
• The new chip, which uses ferroelectric field effect transistor (FeFET) cells, requires 44 times less energy than traditional designs to perform an equivalent number of operations.
• Chips of this kind may later be adapted for cloud computing, but in the near term the main areas of application for the new architecture are in edge computing for transport, industry and IoT.
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White Paper: Sustainability-focused Mobile Technologies for 2030 and Beyond

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An Algorithm to Predict Solar Energy Generation

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E-Reo Brings Digital Life to Indigenous Languages

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Khiops: Simple and Automated Machine Learning

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FIND, a Search Tool That Uses Generative AI to Answers the Pros’ Questions

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“Augmented” Virtual Reality for User Tests

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