'Interoperability' is a big word. Throw in 'cross-chain' before it and it's a mouthful. But get used to it, because it is the key to unlocking the full potential of blockchain technologies, by getting the different chains and networks to communicate efficiently and effectively.

Now, with AI in the picture, it takes things up a notch by making smart contracts smarter: it can automate processes in the realms of finance, supply chain, and data analysis.

Here, we highlight four successful real-world applications of AI and blockchain, and how it is already proving to change the Web3 crypto game.

Chainlink’s Oracle Network

Credit: Chainlink

Chainlink leverages artificial intelligence (AI) to create highly reliable oracles that can connect AI smart contracts on different blockchains. By applying machine learning algorithms, Chainlink ensures accurate data feeds and reduces the chances of tampering.

One great example is Arbol, a crop insurance platform that leverages Chainlink's decentralised oracle network to provide farmers with parametric insurance.

This is how it works:

  1. Data collection: Chainlink's oracle network gathers real-time weather data from multiple reliable sources, such as weather stations and satellites. This data includes temperature, rainfall, humidity, and other relevant parameters.
  2. AI analysis: The collected data is then processed using AI algorithms to assess crop health and predict potential yield losses due to adverse weather.
  3. Smart contract execution: The AI-powered analysis is used to trigger parametric insurance smart contracts on the blockchain. These contracts automatically send payouts to farmers when pre-defined weather thresholds are met, indicating a high probability of crop damage.
  4. Decentralised claims processing: The automated claims process removes the need for manual (and potentially erroneous) entries, and reduces the risk of fraud or delays.

The benefits are aplenty. With tamper-proof data and automated 'underwriting', farmers get the quick financial support they need to subsist on whenever extreme weather conditions occur, and the application of AI oracles inspires trust in the insurance process.

Fetch.ai & Bosch

Fetch.ai, an AI-powered blockchain platform, and Bosch, a global name in engineering and technology, presents an excellent case study of a successful partnership between AI and blockchain.

Fetch.ai leverages machine learning to create autonomous economic agents that can perform tasks such as data sharing and transactions across multiple blockchains.

This collaboration aims to develop a decentralised network for IoT devices, enabling seamless communication and transactions between different blockchain ecosystems.

What problems does the partnership solve:

How the solution works:

The partnership leverages Fetch.ai's Autonomous Economic Agent (AEA) framework and Bosch's expertise in industrial technology to build a decentralised network of intelligent agents. These agents can autonomously communicate, negotiate, and collaborate to optimise various industrial processes.

For example, in supply chain, AEAs can autonomously negotiate supply contracts, plan the best logistics routes, and manage inventory levels. That improves cost savings and efficiency. It can also help regulate energy consumption and sustainability efforts by dynamically adjusting energy usage based on real-time demand and supply.

Polkadot’s AI-Powered Substrate

Credits: Polkadot blog
Credit: Polkadot blog

Polkadot uses AI to manage its multi-chain environment, optimising network performance and automating the seamless interoperability between parachains. AI-driven analytics enhance security and predict potential network threats.

Astar Network, a leading Polkadot parachain, leverages Substrate's flexibility and Polkadot's interoperability to implement the dAppStaking initiative. It allows users to stake their tokens not only on the Astar Network itself, but also on the decentralised applications (dApps) built on top of it.

This is how it works:

  1. Substrate flexibility: Astar Network uses Substrate's modular framework to create a custom runtime that includes the logic for dAppStaking. This allows them to define their own unique tokenomics and incentivise dApp developers and users.
  2. AI-powered optimisation: To ensure the efficient allocation of staking rewards, Astar Network employs AI algorithms. These algorithms analyse various factors, such as dApp usage, transaction volume, and community engagement, to determine which dApps deserve higher rewards. This incentivises dApp developers to create high-quality applications and attracts users to actively participate in the ecosystem.
  3. Polkadot interoperability: Astar Network's connection to Polkadot allows seamless interaction with other parachains and assets in the Polkadot ecosystem. Users can easily transfer their tokens between different parachains and participate in dAppStaking on Astar Network, regardless of which parachain they hold their assets on.

With Polkadot's AI-powered substrate, developers can earn a direct revenue stream just by building dApps on the Astar Network, and on the users' part, there could be greater levels of engagement as they feel compelled to interact with such dApps to bag more staking rewards.

Did You Know? aelf is in on the AI blockchain Action Too!

Since the earlier part of this year, aelf has announced its new chapter on the AI frontier, by employing large language model capabilities to enhance the blockchain's 'smartness' and trainability. At the core of it is a groundbreaking partnership between aelf and AgentLayer, the world's first decentralised network and AI protocol provider, to realise a common goal of a permissionless network for AI agents.

At this time of writing, aelf is accelerating the growth of a decentralised AI infrastructure that facilitates the development and deployment of AI-powered dApps. In turn, this creates a favourable environment to build more efficient, scalable and secure dApps for users.

With an in-house developer-friendly toolkit at hand, dApp builders can expect a smooth transition into aelf's brand new AI future, and the community can also expect to build upon these new technologies.

Although it's still in its early phases, aelf's shift into AI is promising a host of benefits:

  • Advanced task automation that will see reduced human bias and fairer validations
  • Lower barriers to entry for developers looking to supercharge their dApps on aelf, as they get to bank on AI technologies to ease smart contract creation and get on-demand support
  • Highly intuitive user-experience to meet the needs of a growing user base, with intelligent, personalisation features in tow
  • Rigorous security protocols to keep fraud and malicious activities at bay, and promote peace of mind

DeFi projects that already exist on aelf's layer 1 AI blockchain, such as Forest and Project Schrödinger, are set to benefit from the introduction of AI technologies too. Do stay tuned to the blog space for breaking news on this front!

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*Disclaimer: The information provided on this blog does not constitute investment advice, financial advice, trading advice, or any other form of professional advice. Aelf makes no guarantees or warranties about the accuracy, completeness, or timeliness of the information on this blog. You should not make any investment decisions based solely on the information provided on this blog. You should always consult with a qualified financial or legal advisor before making any investment decisions.

About aelf

aelf, an AI-enhanced Layer 1 blockchain network, leverages the robust C# programming language for efficiency and scalability across its sophisticated multi-layered architecture. Founded in 2017 with its global hub in Singapore, aelf is a pioneer in the industry, leading Asia in evolving blockchain with state-of-the-art AI integration and modular Layer 2 ZK Rollup technology, ensuring an efficient, low-cost, and highly secure platform that is both developer and end-user friendly. Aligned with its progressive vision, aelf is committed to fostering innovation within its ecosystem and advancing Web3 and AI technology adoption.

For more information about aelf, please refer to our Whitepaper V2.0.

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