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Artificial Intelligence (AI) tools, including Large Language Models (LLMs), have become essential for answering questions, analyzing code, and completing various tasks. However, due to privacy and security concerns, many companies restrict employees from using these tools. While encrypting data enhances security, it is often avoided due to the computational challenges it presents. At this point, a new project named Nillion offers a decentralized network that addresses these issues while ensuring secure data processing.
What Is Nillion?
Nillion is a decentralized network designed to enhance data security while maintaining high computational efficiency. Unlike traditional encryption methods, it does not require data to be decrypted before processing, which boosts both privacy and performance.
The project is founded by a team specialized in blockchain, finance, cryptography, and technology. Key figures include Andrew Masanto, Alex Page, Andrew Yeoh, and others, whose experiences at firms like Goldman Sachs and Uber lend credibility and expertise to the initiative.
How Does Nillion Enhance Data Security?
Nillion presents an innovative method for securely processing sensitive data. By utilizing Privacy-Enhancing Technologies (PETs) such as Multi-Party Computation (MPC), it can process data without decryption, ensuring sensitive information remains protected.
MPC allows multiple parties to perform joint computations without revealing their individual inputs. For instance, the Millionaires Problem introduced by Andrew Yao in 1982 enables two individuals to compare their wealth without disclosing their net worths. Nillion applies this principle on a large scale, making it suitable for industries that require high levels of data security.
