Bringing AI Training Out of the Cloud and Onto Your Phone
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Efforts underway to enable on-device training of neural networks and large language models directly on smartphones without cloud connectivity
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Local on-device training can enable personalized and privacy-preserving AI capabilities tailored to individual usage patterns
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Techniques like federated learning, selective weight updating, and model compression aim to make complex model training feasible on resource-constrained mobile devices
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Potential applications include personalized speech recognition, intrusion detection systems, app capability inference and more
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2024 may see breakthroughs bringing neural network training out of giant cloud data centers and into people's pockets via their personal mobile devices