👉 Guess computing is a decentralized and privacy-focused approach to machine learning that enables collaborative model training without sharing raw data. Instead of centralizing data on servers, it distributes computations across a network of devices, such as smartphones or edge servers, where each participant performs local computations on their own data. These devices communicate with a central coordinator to aggregate results, ensuring that individual data remains private and never leaves their local environment. This method enhances privacy, reduces data transmission costs, and allows for training on larger, more diverse datasets while maintaining control over sensitive information. It's particularly valuable in scenarios like healthcare or finance, where data privacy is paramount.
