Virginia Tech Researcher Aims To Let Us Keep Our AI Cake & Eat It, Too
, we’re often focused on autonomous vehicles. Because Tesla has been chasing autonomy along with battery-electric vehicles, the topics seem to go hand-in-hand, with some people considering them inextricably linked. For some of us, the idea of a gas-powered self-driving car or an EV without any autonomy features is a sort of heresy.
The significant amount of energy required for training AI models highlights the importance of developing more energy-efficient methods for AI to reduce its carbon footprint and move towards a more sustainable future. This innovative approach involves implementing collaborative AI algorithms using a distributed machine learning technique. By leveraging this technology, the research team aims to reduce the energy consumption associated with traditional AI, ultimately working towards a more sustainable future for the field. With the development of green FL, the hope is that AI can be utilized without compromising efforts towards environmental sustainability.
Among these solutions is federated learning. a distributed machine learning approach where the model or algorithm is trained using data that is stored on multiple, decentralized devices instead of a centralized location or cloud server. Rather than sending data to a central location, the data remains on the device and the model is trained where it was collected.
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