Analysis of the Commercial Prospects of AI and Homomorphic Encryption

Recent statistics on the discussion intensity and price changes of several major cryptocurrencies have been compiled. The data shows that the discussion frequency of Bitcoin slightly decreased last week, but its price increased slightly. The discussion intensity of Ethereum has risen, but its price has dropped. Both the discussion intensity and price of TON have declined.

Homomorphic Encryption(FHE), as an emerging cryptographic technology, is attracting widespread attention. It allows computations to be performed directly on encrypted data without the need for decryption, providing strong support for privacy protection and data processing. FHE has broad application prospects in multiple fields such as finance, healthcare, and cloud computing, especially in scenarios that require the protection of sensitive data.

The core advantage of FHE lies in its ability to protect privacy. For example, a company can provide encrypted data to another company for analysis and computation without worrying about data leakage. This mechanism is particularly important in industries such as finance and healthcare. In the fields of cloud computing and artificial intelligence, FHE can also achieve secure multi-party computation. Additionally, FHE can be applied to blockchain technology to enhance the transparency and security of data processing.

Compared to other privacy protection technologies such as zero-knowledge proofs and multiparty computation, FHE has advantages in supporting complex computational tasks. However, FHE still faces some challenges in practical applications, mainly including:

1. High computational overhead: FHE requires a large amount of computational resources, making it difficult to meet real-time computing demands.

2. Limited operational capability: Currently, FHE is mainly suitable for linear and simple polynomial calculations, with insufficient support for complex nonlinear operations.

3. Multi-user support complexity: When involving multi-user datasets, the system complexity increases significantly.

In the field of artificial intelligence, FHE provides a new solution for data privacy protection. Users can analyze data using cloud AI services while protecting sensitive information. This feature is particularly important under regulations such as GDPR.

Currently, several projects are applying FHE technology in the blockchain field, mainly focusing on on-chain privacy, AI training data privacy, and on-chain voting privacy. Some representative projects include:

• A FHE development platform focused on Boolean operations and low-word-length integer operations
• Developing a new type of smart contract language and FHE library project
• A solution for privacy protection in AI computing networks using FHE
• A decentralized privacy protection platform that combines FHE and AI
• Ethereum Layer 2 scaling solution supporting FHE

Despite the challenges that FHE currently faces in commercial applications, these issues are expected to be gradually resolved through hardware acceleration and algorithm optimization. With the development of blockchain technology, FHE will play an increasingly important role in privacy protection and secure computing. In the future, FHE is expected to become a core technology supporting privacy-preserving computation, bringing revolutionary breakthroughs to data security.