Taking advantage of the upcoming launch of the Nillion mainnet, I curiously studied the origin of the Blind Computation concept and its relationship with other related concepts such as MPC and FHE as privacy computing. Blind Computation first appeared mostly as the concept of Blind Quantum Computation, and can also be considered to have originated from the field of quantum computing. Related papers that can be traced back to between 2001 and 2003（ https://arxiv.org/abs/quant-ph/0309152 ）. Its definition is to process and calculate data without exposing its content. That is to say, to make the executor of the calculation "unaware" of the data being processed. The core of this concept is to maintain the confidentiality of input, output, and even computational logic during the calculation process, without being understood by the party performing the calculation. It sounds very similar to FHE (Fully Homomorphic Encryption) before, yes, they want to solve similar problems. However, Blind Computation does not have a particularly unique and formal cryptographic definition, and is sometimes a broad and conceptual term. FHE is a very specific cryptographic tool or system that can perform arithmetic operations (addition, multiplication, or expandable to any circuit calculation) on ciphertext without decrypting it, and finally decrypt the operation result to obtain the same result as directly operating on plaintext. So from the broad concept of blind computing, it actually requires the use of various specific cryptographic schemes to achieve, such as MPC ZKP, TEE, or FHE. In short, Blind Computation is a general term. And Nillion's blind computing solution aims to achieve privacy computing and storage in multi node distributed scenarios, using tools such as secret sharing, MPC, TEE, etc. to achieve "nodes cannot see plaintext data locally, but collaborative computing can be completed". It adopts a dual layer architecture design, consisting of a privacy computing layer "Petnet" and a coordination layer "nilChain". In addition, a series of blind modules have been defined within the architecture as the core components that perform specific functions. Privacy computing layer "Petnet": composed of a distributed node network, responsible for actual data storage and computation. Petnet utilizes various privacy enhancing technologies (PET) to ensure that data is processed in encrypted or split state. Petnet organizes nodes into clusters on demand to perform specific tasks, with each cluster viewed as an independent blind computing unit, providing data sharding processing across multiple nodes. Coordination layer 'nilChain': a blockchain built on Cosmos SDK for global resource management and incentive mechanisms. NilChain itself does not handle any private data or computing logic, but acts as the "operating system" of the network, responsible for task scheduling, node management, and payment settlement. For example, nilChain records the staking and reputation of nodes, assigns computing tasks to appropriate Petnet node clusters, and processes user payments and node rewards. The blind computing capability provided by Nillion can theoretically achieve many application scenarios that require data privacy, such as "privacy enhanced AI applications," "privacy DeFi and transactions," "encrypted data analysis and computation," and so on. However, in order for Nillion to achieve its technological proposition, it needs to break through in three aspects simultaneously: security, performance, and ease of use. There are industry recognized difficulties in every aspect, such as the classic challenge of MPC being communication complexity, the challenge of FHE being computational overhead, and the challenge of TEE being trustworthy infrastructure. Nillion has chosen a path of integrated innovation, which, although theoretically complementary to its weaknesses, also adds various technological risks. In future development, how to prove the security and reliability of its protocol and achieve efficient performance in real environments will be a key issue that the Nillion team must address. And more importantly, whether developers can build meaningful and widely popular privacy applications after the main network goes online.