Intelligence demonstrated by machines as opposed to human beings is classified as Artificial Intelligence. This is a basic conceptual definition, however, and there are degrees to AI competency. In other words, gradients of “intelligence” can be delineated based on what a system or machine can do. The three basic categories used to classify AI systems and machines are as follows:
Even though the AI economy is projected to grow by billions, AI itself, in general, is not widely available to the public as a tool. This is in large part due to the concentration of the share of AI markets in the hands of a few major players, which brings about stagnation in terms of development and application. This is because there are serious scalability and innovation limitations in closed, centralized systems, and unfettered access to AI by users working in different industries and verticals with different research and business interests can help the AI economy as a whole take considerable steps forward.
Openfabric has developed a blockchain-centric AI ecosystem that seeks to take advantage of the features of Distributed Ledger Technology and bring those benefits and applications to the public. The selection of this technology is not by chance; instead, it is a deliberate choice that can help us address known challenges in the AI domain. We talk about some of these challenges below.
By being a decentralized ecosystem, no central authority controls the location of data or its processing. This provides significant improvements in execution and governance protocols which are further boosted by storage scalability wins. Siloed data, centralized operation, and single points of failure will all become things of the past.
Many of the key hurdles in the advancement of Artificial Intelligence are data-related. However, they are not simply the immense need for massive amounts of data to train and execute AI algorithms – although that is difficult enough to accommodate –there are also privacy and integrity concerns. The blockchain can help overcome data privacy, provenance, and security issues seamlessly as a built-in feature of any system.
With data security addressed, incentives for AI Innovators and Data Providers abound, especially when it comes to working in a collaborative environment with Service Consumers.
Interoperability is the cornerstone of the incentivized AI agent marketplace. Interoperability allows for the innovative collaboration of complex AI agents to deliver mutually beneficial outcomes. Together, the variety and versatility of the marketplace foster an environment where Service Consumers proverbially “shop” for the tools, applications, and solutions that best suit their needs.
The standardization of interfaces for collaboration allows for superior algorithmic composition in addition to providing better structure compared to centralized approaches. You can think of it as customizable services provision down to the user level rather than the wholesale, cookie-cutter approach preferred by large corporations.
No matter how good an application or service is, the golden rule holds true: simplification is difficult and complexity is easy. Openfabric AI has been designed with ease of use, usability, and integrations for end-users to interact with AI in a developer-friendly way in mind.
A high degree of trustfulness is provided by a blockchain-driven platform. Another satisfied criterion is that of scalability. By virtue of being decentralized, Infrastructure Provider stakeholders have an incentivized market environment to participate in by renting out underutilized infrastructure.
Openfabric promotes innovation with a robust, fair, and built-in exchange mechanism to cater to the demand and supply of AI services provided by its network of AI Innovator stakeholders.
One of the larger challenges with AI is the sourcing of data to train AI algorithms. By utilizing the blockchain to provide a secure, transparent, and trustless ecosystem, Openfabric puts in place the infrastructure required to support massive data flows. This is in conjunction with a Smart Market and a collaborative Innovation Engine that creates the conditions for superior data streams to emerge.
Blockchain technology gives us the underlying infrastructure for a seamless and secure flow of encrypted data. This is a technical leap forward that facilitates encrypted data flow and it opens the doorway to solving a key problem faced by anyone working in the AI or data spaces, which is access to private data in different jurisdictions. With the blockchain-based Openfabric solution it will no longer be required for data to move unencrypted for analysis. Algorithms can run behind firewalls in what would be an “AI at the Edge” and localized implementation near the Service Consumer.
Furthermore, this opens the pathway to further development for Local, Federated, and Cooperative models to emerge in a safe and secure ecosystem that is not hindered by:
The blockchain essentially becomes the access layer in the provision of performance, transparency, and security in data processing. The Openfabric ecosystem promotes the seamless integration between Data Providers and AI Innovators. With major challenges being addressed regarding interoperability, Smart Economy, and security, Openfabric has the potential to create an innovation engine that will secure the intellectual property of developers and stimulate fair competition between all participants within the ecosystem.
To learn more about the Internet of AI as imagined by Openfabric, please visit https://openfabric.ai.