Today, we live in a digital era - however, prevailing AI ecosystems are exhibiting severe limitations, particularly those concerning fragmentation, isolation, and the lack of an environment for stimulating evolution and mass-adoption. To solve this problem, Openfabric challenges the most difficult problems faced by AI platforms:
Ensure that there is no central entity that controls the location of data or information processing.
Protect end-user privacy and guarantee intellectual property rights.
Implement the use of standardized interfaces, to allow multiple AI agents to cooperate and connect in order to provide relevant answers to complex problems.
Simplify the interactions between end-users and AIs by providing straightforward, non-technical flows.
Create a built-in robust exchange medium that facilitates fair transactions between supply-and-demand of AI services.
Expand network capabilities by allowing network participants to rent their computing power for the execution and training of AIs.
Experience the future of the internet in which AI algorithms are able to connect, combine, and evolve in an open environment, padding the path toward artificial general intelligence. Openfabric is the world's first platform that provides straightforward access to AI solutions through the elimination of cumbersome technical hurdles. With Openfabric technology, a user can access AI solutions with the simple click of a button.
Openfabric is a decentralized AI platform in which the collaboration between AI innovators, data providers, businesses, and infrastructure providers will facilitate the creation and use of new intelligent algorithms and services.
The service consumer represents the end-user who needs to solve particular business problems and enrich their products or services with an extra layer of intelligence. The platform serves to simplify their experience by eliminating the prerequisites of having technical skill or owning hardware equipment that is normally required to run and train AI.
AI innovators utilize their expertise to create elaborate, practical AI algorithms that are capable of solving complex business problems. The platform incentivizes the innovator to focus on delivering high-quality solutions and to engage in cooperation instead of competition, by reusing algorithms deployed by others in order to build ever-more intricate and general AI solutions.
Infrastructure providers bring with them all the platform hardware capabilities needed to run and train AIs. Solving challenging and complex problems requires a considerable amount of computing power, which can only be achieved through the joint participation of multiple providers.
Data providers ensure the vast amount of data required for training and testing AI algorithms. Companies that possess consistent datasets can make a profit by licensing them on the platform, to be used by the innovators and data providers.
Openfabric is an ecosystem that harnesses the power of blockchain, distributed ontologies, advanced cryptography, and a trusted execution environment by developing a novel infrastructure that is uniquely capable of supporting the authentic AI revolution.
Openfabric lowers the adoption barrier by reducing the infrastructure demands and technical know-how required to utilise AI algorithms. This aspect empowers the end-users to operate with a new generation of intelligence-driven products and tools accessible through the built-in peer-to-peer marketplace.
Securing intellectual property and stimulating fair competition amongst innovators are the key factors that work to coagulate large, vibrant, and collaborative communities. This aspect embodies the real catalyst which drives the evolution of intelligent algorithm solutions.
Motivated by the goal of decentralization, Openfabric brings together the concepts of scalability and AI algorithm execution. Any infrastructure provider that adheres to the requirements of the ecosystem will take part in this endeavor.
In Openfabric, a Bayesian reputation model supervises the quality and performance of products and services through a reputation score that is computed based on community feedback. It also serves to increase collaboration amongst participants in a safe environment, without relying on a centralized authority.
In order to achieve high-quality, valuable and reliable results, the support of an economic environment is required to cover innovator expenses through the monetization of their work. By satisfying the financial aspect, innovators can then dedicate their time and effort toward exploring, formulating, and creating elaborate solutions which accelerate the ecosystem's growth.
The Openfabric marketplace provides a uniform, intuitive and simplified user experience, which allows the execution of AIs without the necessity of installing, configuring or customizing anything. It consolidates the business relationship between the supply-and-demand of AI services, innovators, infrastructure providers, end-users, and businesses.
Privacy is an essential attribute of Openfabric, which stems from the fact that algorithms and data sets are decrypted only inside the TEE, so neither the platform nor the executor has access to it.
Considering enterprise adoption of edge technologies is slow, expensive and disruptive, Openfabric provisions connectors minimising the integration friction.
The distributed ledger ensures undeniable contracts and unforgeable history between the platform's stakeholders. It also serves as the underlying layer for access control and identification mechanisms. The platform is orchestrated by a decentralized operating system (DOS) which manages network resources, services and processes, and coordinates the proper functioning of the system.
Nash equilibrium is achieved when infrastructure providers offer excellent services, innovators generate high-quality algorithms the community is willing to pay for, and service consumers efficiently combine algorithms to obtain solutions for their specific use cases.
Achievements & Goals
The idea of Openfabric is born.
Understanding the needs, constraints, and next steps toward progressing AI ecosystems.
Business research for determining platform stakeholders.
The foundation of the economic system and incentive mechanics.
Scientific validation of the core components.
Publishing research papers on peer-reviewed computer science journals.
An Ontology Model for Interoperability and Multi-organization Data Exchange - published on Advances in Intelligent Systems and Computing
Dynamic Consensus: Increasing Blockchain Adaptability to Enterprise Applications - published on Advances in Intelligent Systems and Computing
Fundamental macro components required for building the Openfabric ecosystem.
Openfabric technical whitepaper
New Openfabric website
Practical validation of the Openfabric model
Technical assessment of various blockchain and execution environment models
Experimenting and quantitative/qualitative evaluation of the proposed architecture
Industrial Partnership Agreement