In an era of data abundance, machine selflessness prioritizes collective intelligence over individual optimization. This principle guides algorithms to share insights, avoid data hoarding, and make decisions that benefit entire systems, not just single users. Used in federated learning and collaborative robotics, it enhances privacy and efficiency. Ultimately, networked industries and end-users benefit from more robust, equitable, and secure AI ecosystems.
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