Recently, there has been significant activity in the privacy computing field. Leading institutions like Grayscale continue to focus on the FHE (Fully Homomorphic Encryption) direction, and the underlying logic is quite clear—fully homomorphic encryption technology, as a cutting-edge track, is becoming an area where capital is rapidly investing.

From a technical perspective, FHE addresses a fundamental challenge: performing computations directly on encrypted data without decrypting it. This naturally has applications in privacy protection and data security. Currently, the entire ecosystem is still in its early stages, with relatively small project sizes, which also indicates that there is indeed room for institutional allocation.

More interestingly, around 2026, the trend of integration between AI and cryptocurrencies is gradually becoming clearer. FHE happens to be at the intersection of these two fields—supporting AI model training and inference in privacy-preserving environments, while naturally aligning with the decentralized nature of blockchain. Progress in projects like Mind Network is also validating the feasibility of this direction.

Of course, any emerging track carries uncertainties. But from the rhythm of institutional deployment and the evolution of technological maturity, the FHE track is indeed worth continuous observation in the future. For long-term participants, the key is to understand the essence of the technology rather than short-term fluctuations.