FHE COMPUTER
WITH MARKETPLACE
>1: Component Based FHE App
Applications running on Fair Math Computer leverage FHE components with each component representing a specific algorithm, circuit, or function capable of processing encrypted and plaintext data. These components range from simple functions like square roots to complex algorithms for handling arrays and matrices.
2: FHE Market
It serves as the Application Layer, providing a platform for applications built from FHE components, ensuring a modular and efficient structure.
Additionally, each time an application is executed, royalties are distributed to the developers of the individual components used, fostering a collaborative and incentivized ecosystem for creators.
>3: Orchestration Layer
The orchestration layer optimizes app execution processing and manages fault-tolerance policies for nodes, ensuring efficient task execution and coordination. It also implements robust fault-tolerance mechanisms to maintain overall system reliability and minimize the impact of potential setbacks on the nodes' framework.
>4: Execution Layer
The execution layer of the Fair Math Computer is composed of Fair Math actors, which serve as the core computational units of the system. Each actor can be specialized to handle specific FHE components or function as a general-purpose computational node, capable of processing a wide range of tasks. This flexible design allows for optimized execution of component-specific workloads while also supporting broader computations, ensuring efficiency and scalability within the network.
// info
The concept of decentralized computer is incredibly powerful, but without the ability to process private input securely, its use cases are limited. Fair Math unlocks new possibilities, making confidential computation accessible and pushing technology to the next level.
Manifesto
Our Goals and Vision
Our goal is to build a scalable, open-source ecosystem that enables broad access to privacy-preserving computing. By overcoming barriers related to privacy and confidentiality, we aim to unlock new use cases and drive innovation. Fair Math strives to serve as the foundational platform for the next generation of secure and decentralized applications.
>READ MORE
Fair Math Actor
Computational nodes are the heart of the computer, forming the execution layer. These nodes participate in computations and are rewarded for their work.
Developer
Developing FHE components essential and provides an opportunity to earn fees if those components are selected for building applications.
Validator
Validators are responsible for securing the network, verifying transactions, participating in block creation and executing the consensus mechanism.
>Building a User-Friendly Ecosystem for Privacy-Preserving Technologies with Fully Homomorphic Encryption (FHE)
>
Fair Math is a research company with an open-source and community-oriented approach, dedicated to addressing privacy challenges in the modern world. Our focus lies in developing privacy-preserving technologies rooted in Fully Homomorphic Encryption
Our team consists of cryptography and decentralization enthusiasts with a strong background in developing state-of-the-art ZKP toolkits and libraries for the Web3 community. We believe that the future of the Web3 should be built on a clear and verifiable foundation, and we’re building the part of it which we are good at.
>> FHERMA: Motivating developers through competition
> We're developing the Polycircuit library with the support of the FHERMA platform, where we host FHE challenges. FHERMA is jointly developed by Fair Math & OpenFHE Teams.
>MORE INFOThis initiative unites FHE developers from various communities, creating the largest FHE community. By fostering a competitive environment, we encourage developers to continuously enhance their algorithms and contribute to the improvement of Polycircuit.
In the Fair Math ecosystem, FHERMA acts as a transparent and fair benchmarking platform for adding new components and updating existing ones within the Polycircuit Platform. This ensures continuous improvement and optimization of FHE components for privacy-preserving applications.
Real-world applications of Web3 and Web2 technologies in various industries and everyday scenarios.
Darkpool
>
Protect trading information, prevent price manipulation and data leaks.
Privacy preserving AI
>
Data security in using AI to joint data analysis and build models without violating privacy.
Private DeFi
>
Conduct transactions and invest in digital assets without disclosing personal information.
FHE Vector Database
>
Ensures secure storage of sensitive data while allowing users confidential access through private requests.
>
We admire the FHE community and we love open-source. That’s why we’re so committed to build the foundation for real-world FHE-enabled applications and protocols for everyone to use freely.
