In order to achieve high-quality, valuable, and reliable results, the support of an economic environment is required to cover innovators’ 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.
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.
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 that 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 unforgettable 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 to coordinate 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.
In order to achieve high-quality, valuable, and reliable results, the support of an economic environment is required to cover innovators’ 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.
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.
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 to coordinate the proper functioning of the system.
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 to coordinate the proper functioning of the system.
Ensure there is no central entity controling the location of data or information processing.
Simplify interactions between end-users and AIs by providing straightforward, nontechnical flows.
Protect end-user privacy and guarantee intellectual property rights.
Create a built-in robust exchange medium that facilitates fair transactions between supply-and-demand of AI services.
Implement the use of standardized interfaces, to allow multiple AI agents to cooperate and connect in order to provide relevant answers to complex problems.
Expand network capabilities by allowing network participants to rent their computing power for the execution and training of AIs.
Features | Centralized | Decentralized | |||||||||
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IBM Watson | Google AI | Azure AI | Amazon ML | Singularity | Ocean Protocol | Effect AI | DeepBrain | Thought Network | Openfabric | ||
![]() | Governance | ||||||||||
Execution | |||||||||||
Storage | |||||||||||
![]() | Ownership | ||||||||||
Privacy | |||||||||||
![]() | Scalability | ||||||||||
Trustfulness | |||||||||||
![]() | Developer-friendly | ||||||||||
User-friendly | |||||||||||
Tools-integration | |||||||||||
![]() | Fair market | ||||||||||
Open market | |||||||||||
Marketplace | |||||||||||
![]() | Algorithm composition | ||||||||||
Structural level | |||||||||||
Open source Framework support |