Leveraging edge computing, where data processing occurs on or near the device where data is generated, offers a privacy-first approach to AI and machine learning. This minimizes the need to transmit sensitive data over networks or store it centrally, significantly reducing privacy risks. While there may be concerns about the computational limitations of edge devices, advancements in hardware and software optimization ensure this approach does not inherently compromise efficiency.
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