Discover how AI is reshaping the cryptocurrency landscape with the top 10 projects leading the way in solving real-world challenges.

The incorporation of artificial intelligence has opened up a world of opportunities as the cryptocurrency industry develops. The ten most promising cryptocurrencies that are using artificial intelligence (AI) to solve a variety of real-world problems will be covered in this article.


Intrinsic (INJ)

A cryptocurrency project called Injective (INJ) is primarily concerned with finance and the creation of apps for decentralized finance (DeFi). Users can participate in various financial activities within the DeFi ecosystem with the help of Injective. It trades foreign exchange futures, margin, and derivatives on many blockchain networks. Injective’s native coin, INJ, verifies and safeguards the transactional integrity of the blockchain. In addition, it is used for governance and gives token owners the ability to influence decisions.

Token for render (RNDR)

Render leverages the processing power of cryptocurrency miners who are prepared to rent out their Graphics Processing Units (GPUs) in order to make computer graphics rendering easier. With this method, users and artists can access the GPU resources they require. To use the GPU power that miners are offering, users must pay RNDR.

ROSE (Oasis Network)

A proof-of-stake (PoS) blockchain network called Oasis Network was created expressly to support open finance, which will increase privacy. The Oasis Network’s native coin is called ROSE. ROSE is used by users for a variety of things, including as staking, transaction fees, and network ecosystem participation. As the “first privacy-enabled blockchain platform for open finance and a responsible data economy,” Oasis Network is well-known.

DKA, or dKargo

dKargo is a blockchain-based platform that uses AI to solve trust-related issues in the logistics industry. The platform accomplishes this by using the immutability of blockchain technology to deliver reliable and authentic data to users. The native cryptocurrency of dKargo is called DKA, and it is used as a means of exchange.

Trail of Origin (TRAC)

OriginTrail is mostly concerned with the supply market sector. The main goal of the AI crypto project is to make it easier to trace products in real time across the supply chain. This is accomplished by boosting transparency and traceability, doing away with the need for conventional documentation, and keeping an unchangeable record of the product status on the blockchain. Spending OriginTrail’s native coin, TRAC, allows users to access its services.

AGIX SingularityNet

SingularityNET is a blockchain platform where users can either buy AGIX, the platform’s own coin, to integrate AI capabilities into their own applications or earn them by offering AI services and models. Users of the platform can develop and offer AI services.

The Ocean Protocol

Ocean Protocol, like SingularityNet, enables the exchange and commercialization of data and data-related services. People can share data and data-based services with one other while still keeping ownership and control over their own data.

EFT (Fetch.ai)

A blockchain-based platform called Fetch.ai uses machine learning and artificial intelligence to automate a variety of commercial processes. Trading and data processing are among the tasks. The native cryptocurrency, FET, functions as the payment method for carrying out transactions and facilitating network interaction inside this ecosystem.

AKT, or Akash Network

Akash Network, a decentralized cloud computing network, functions as a marketplace. It serves as a go-between for those in need of cloud computing resources and those who supply them. Blockchain technology is what makes this link possible.

The GRT (Graph)

The Graph is used to index and query data from several blockchains in a manner akin to how Google retrieves and indexes content from webpages. The protocol aims to improve the accessibility and efficiency of blockchain data indexing. The Graph divides blockchain data into smaller chunks known as “subgraphs” in order to accomplish this. The data is easy to handle and query with this method.

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