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DAIN AI, Geo-dispersed Public Computing Network Governed Through Blockchain

Just as electricity and also the internet remodeled everything, artificial intelligence (AI) and blockchain would disrupt each business within the coming years. to steer this transformation, Introducing DAIN, a decentralised, geographically distributed network specialised in AI issues and ruled through blockchain.

DAIN is a new generation artificial intelligence platform enabling the efficient utilization of the computing resources of any device to solve complex computational problems. DAIN does not have its own computing resources. Instead, it makes use of free computing resources from any computer or device, from non-public datacenters to smartphones and the Internet of Thing devices.

DAIN, A Decentralized, Geographically Dispersed Network Specialized in AI Problems

Understanding and leverage the chances of an artificial brain with unlimited measurability could be an advanced task. Today is the time for the explanation of DAIN Ecosystem, DAIN Solutions, and DAIN Platform. First DAIN Ecosystem, DAIN is created, built, and grown by and for its users. Just like the internet, DAIN users can outline what DAIN can become within the future. Users will participate during this scheme by taking part in completely different roles.

Then DAIN Solutions, The business toolbox designed to offer out-of-the-box value to DAIN users. It aims to contour the democratisation of AI and modify new business models. Last, DAIN Platform, The core underlying infrastructure that allows the ecosystem and also the creation of solutions. Its mission is to determine a secure marketplace for computing resources, data, and AI models.

Designed to Interact with Two Kinds of Users, End-users, and Institutions

DAIN is conceptually designed to interact with two kinds of users, end-users, and institutions (private companies or any other kind of institution, such as universities or research centers). End Users fuel the computational resources market, sharing the free computing the capacity of their devices to cover institutions’ requests for service, receiving a reward (tokens) as payment.

Institutions make requests for service to the network, consuming its computational resources. Depending on the type of service request, they can be divided into Producers and Consumers. First, Producers, create new AI models trained in DAIN using their own data and/or data provided by the network members, paying tokens in exchange for the usage of the required computing resources or data.

These solutions can be created only for their own consumption, or they can be exposed in the marketplace at any time to generate new revenue streams. Then second is Consumers, Consumers directly access the AI marketplace to reuse existing solutions created by Producers. 

It is relevant to note that while initially, DAIN is expected to grow with each type of user playing the specific roles described, it is not limited to this model. As an example, establishments with their own datacenters or cryptocurrency miners might play the “End User” role and share their computing resources through DAIN, getting DAIN tokens in exchange.

DAIN Platform Technology Solution

As described, DAIN Solutions provide ready-for-use business solutions. This section details the initial set of solutions that will be provided on top of the DAIN platform. Empathy – Engagement platform, Knowledger – AI Marketplace, Soul – Autonomous agents, Psyche – A Zero-Code Artificial Intelligent Journey Platform, and Intuition – Laboratory.

Current technology implementations face many various challenges to be ready to accomplish behavior just like the one represented for DAIN. to deal with them, DAIN implements novel design supported 3 technology pillars, Fog Computing mechanisms over P2P networks composed of doubtless any device with computing capacity (IoT, smartphones, desktops, servers, etc.), enabling the sharing of spare computing capability.

Permissionless scalable Distributed Ledger Technology (DLT) to support the tokenization and accounting of computing resources, using a new consensus the approach that addresses a number of the most issues of current DLT implementations. Useful-Proof-of-Targeted-Work protocol to produce AI services over decentralised and non-secure open networks.

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