What are the application scenarios for the combination of AI and blockchain?

AI will dramatically increase productivity, while blockchain will provide security and transparency, thus enabling a variety of innovative applications.

Written by: Chainlink

AI and blockchain are two of the most disruptive technologies of our time, with the potential to set off a revolution of innovation across multiple industries and revolutionize economic and social relationships. The combination of blockchain and AI will unlock new application fields. AI will dramatically increase productivity, while blockchain will provide security and transparency, leading to a variety of innovative applications.

According to Spherical Insights, the combination of blockchain and AI will develop into a billion-dollar industry in the next ten years. How these two technologies work together, however, is still an understudied question, so it's worth exploring.

This article will look at AI in the context of blockchain and explore the potential intersection of the two technologies and their value.

The Intersection of AI and Blockchain

Deep learning models are good at processing big data, simulating the cognitive process of the human brain, and using complex neural networks to identify patterns, make predictions, and make decisions. The blockchain network has a transparent, decentralized, and manipulation-resistant transaction settlement layer, which is available immediately after networking, and data stored on it cannot be tampered with, and users can interact with the blockchain in a way that requires no permission and minimizes trust.

*The combination of blockchain and AI will give birth to an automated intelligent decision-making system that outputs very reliable results and triggers operations in the real world based on tamper-proof data. *

The combination of blockchain and AI will unlock a new business model, improve operational efficiency for enterprises, automatically complete repetitive tasks for individuals, exchange data more securely and efficiently, enhance decision-making processes through AI smart contracts, and improve key infrastructure and Trust and transparency in the transaction process.

The combination of AI and blockchain will not only benefit traditional business applications, but also extend to other fields. Combining the powerful analytical capabilities of AI with the advantages of blockchain in terms of security and decentralization, it can be applied to various fields such as education, healthcare, energy, society, agriculture, and urban planning to better make decisions based on data, and Improve resource management efficiency.

AI and blockchain will disrupt a range of traditional industries

Combined Use Cases of AI and Blockchain

This chapter explores a range of potential use cases for the combination of AI and blockchain.

Guaranteed Security

Decentralized infrastructure and blockchain technology can provide cryptographic security for AI systems. We can embed security fences in the AI system to prevent the system from being abused or maliciously manipulated. AI developers can set specific parameters in the code to control the threshold for AI to access various key systems; they can also use tamper-resistant infrastructure such as blockchain, smart contracts, and oracles to create a private key mechanism.

The original intention of the blockchain system is to prevent various malicious attacks and manipulations, and these security mechanisms can also be used to prevent attacks in the AI field. In a centralized system, as long as there is a problem in a certain link, the security of the entire system may be threatened; while the decentralized infrastructure is distributed to multiple nodes and multiple independent private keys, so it is more difficult for attackers to invade the entire system. system.

Blockchain can effectively improve the security of AI applications, so enterprises can fully realize the potential of AI and ensure security through encryption technology.

Track Supply Chain

A smart contract is a computer program deployed and run on the blockchain. The code in the contract specifies the trigger conditions and the results of the trigger. Smart contracts can be executed automatically, so they have special advantages when combined with AI. The AI model is connected to the smart contract, and specific conditions can be predefined to perform tasks, such as: monitoring the inventory situation, and automatically placing an order with an external supplier when the inventory is insufficient.

The combination of blockchain and AI can also digitize paper-based processes and monitor every link from production to delivery in real time to improve transparency and reduce the risk of fraud. Combining AI's predictive analytics capabilities with blockchain will allow businesses to gain better insight into demand patterns, optimize inventory management, and make data-based decisions to reduce costs.

This use case can also be useful in other areas, such as disaster mitigation efforts. Combining AI analysis functions with on-chain supply chain tracking functions can help people-oriented organizations and enterprises optimize resource allocation during disasters, and provide real-time data on the quantity and geographic location of disaster relief materials to improve efficiency and better distribute materials.

Verify the authenticity of the content

The emergence of deep learning models such as DALL-E, Stable Diffusion, and Midjourney has demonstrated the unlimited potential of generating images or other media from text.

While these models give us a glimpse of AI's disruptive innovation potential for productivity and creativity, they could also be used to spread false rumors or fake images or other communication mediums.

The bottom layer of blockchain technology is cryptography and encryption technology, so it can be used to verify the authenticity of media such as images, videos, and text, and encryption technology is used to verify the source of content and whether the content has been tampered with. This cryptographic watermarking technique can also be used to create tamper-proof timestamps that verify the authenticity of message content, origin and time.

If society is to be stable in the future, it will be necessary to be able to distinguish between AI and human-created content. Therefore, cryptographic verification and timestamps can be used to assist decentralized platforms to display, verify and distribute content. Such platforms can also help creators and users build trust in content, ensuring that the medium of information dissemination has not been tampered with, is authentic, and that all historical records are transparent and verifiable.

In addition, on-chain certificates, especially NFT, can effectively solve the problems faced by verifying the authenticity and traceability of digital content. NFTs are unique digital assets that can be used to represent asset ownership and verify the origin of various files such as images, videos, text, and music.

Binding NFT to a certain content allows creators to create digital fingerprints to ensure that the content is traceable on the chain. When content is minted as an NFT, its origin, history of changing hands, and any subsequent modifications become transparent and easily verifiable. Such technologies, once standardized, could enhance accountability for Internet content. Publishers can get more incentives to ensure the authenticity of works, and ordinary people can better distinguish between real and tampered content.

analyze data

The greatest value of blockchain technology is that it can most efficiently guarantee the authenticity of data sources. To ensure data integrity in the long run, the best way is to store data in a highly secure decentralized blockchain network. Therefore, the blockchain is naturally a good big data analysis platform.

As the blockchain increasingly dominates human social and economic activities, the use of complex machine learning models for big data analysis can also handle massive data sets on the chain. These machine learning models can identify megatrends and output useful insights through predictive analytics. This can help companies and individuals make efficient and rational decisions and judge emerging opportunities in the on-chain economy.

In addition, the AI model can also optimize blockchain consensus algorithms including bitcoin, reduce latency and perform operations for blockchain nodes.

Provision of Financial Services

With decentralized finance (DeFi), anyone with an Internet connection can access transparent financial services, conduct peer-to-peer transactions, and interact with immutable smart contracts. The DeFi ecosystem has made great progress, and AI models can take advantage of these increasingly enriched and mature DeFi financial services, perform operations and tasks based on predefined instructions, and conduct transaction settlement.

If a large language model can be securely connected to the Internet, it can also be connected to Web3's on-chain financial technology stack to perform routine tasks such as payment or transactions. Due to the composability of blockchain applications, AI models can execute complex interrelated financial transactions without relying on any intermediaries and opaque traditional financial systems.

In addition, AI can also be used in DeFi applications to automatically execute investment strategies and provide users with innovative financial services using a secure and transparent decentralized infrastructure. AI is good at decision-making, while blockchain is good at recording real-time transaction behavior, so the combination of the two can establish automatic compliance and fraud detection processes based on machine learning algorithms.

Provide health care services

Some blockchains are well-suited for storing sensitive data, and advanced AI models can also use this to analyze health data and identify recurring patterns, and make accurate diagnoses based on medical photos and medical records. In addition, innovative encryption technologies such as homomorphic encryption can also perform operations on data without revealing data privacy.

AI and blockchain technology can securely store and share medical records, medical research data, and other sensitive data, thereby improving the management, privacy, and security of medical data. Researchers in the fields of healthcare and longevity will be able to collaborate more effectively in remote locations with maximum data security.

Blockchain technology can be used as the underlying data storage solution, on which to develop AI diagnostic tools and customize treatment plans, while enhancing data privacy and improving the efficiency and customization of the healthcare system.

Guaranteed Transparency

One of the challenges that current deep learning models face is that the decision-making process is opaque. Because these models are very complex, sometimes with hundreds of billions of parameters, it is difficult for experts to explain why a certain model outputs a specific answer to a specific question.

While this opacity is a fundamental characteristic of deep learning models, and it is ultimately the job of AI researchers to develop AI models that can explain their own decisions, blockchain networks can take advantage of their transparency to some extent to address Problems with AI model opacity.

Blockchain can record data transparently, so it can allow AI models to create a clear framework for operation, analyze audit trails based on algorithmic decision-making models, and use immutable data ledgers to view the data used by models. Ultimately, doing so will further improve the quality of the AI model's recommendation algorithm.

Decentralized data storage

Many AI models rely heavily on large datasets. While data is only one element, it can greatly affect the performance of an AI system. Blockchains such as Filecoin, IPFS, and Arweave can provide decentralized storage solutions, effectively guarantee the quality of training data and accurately trace data. In addition, as mentioned above, innovative encryption techniques can also provide encrypted data sets for deep learning models while protecting data privacy.

Combining blockchain storage solutions with deep learning technology will improve the safety and reliability of AI systems while enhancing transparency and credibility in the decision-making process.

Developing Smart Contracts

With the emergence of AI-assisted development tools such as Github Copilot, the efficiency of smart contract developers has been greatly improved. In addition, it is also possible to integrate AI-driven API interfaces in smart contract applications, analyze real-world sensor data or user sentiment on social media, or create generative models. These will ultimately drive the development of a new generation of Web3 applications. In this demo, Google's AI lead, Laurence Moroney, shows how to use Stable Diffusion and Chainlink Functions to develop an AI art generator for smart contracts.

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AI can also help game developers create entire game worlds, in-game assets, NPCs, and game script events to unlock new Web3 gaming experiences. In addition, developers can also use natural language and generative AI models to develop game mechanics and embed these parameters into the game's on-chain logic. A group of game enthusiasts can use generative AI models to assist in writing open source code and jointly develop games.

Challenges and considerations of AI combined with blockchain

While the combination of AI and blockchain technology can bring many benefits to many industries, there are still some challenges that need to be overcome to realize the potential of both. AI models have always had a problem collecting data because they have to feed into multiple different datasets. To perfectly combine AI and blockchain, it is necessary to solve the interoperability problem between these two platforms and establish standards to enhance the connectivity and compatibility between these two technologies.

In addition, the data privacy framework needs to be upgraded to solve the problems encountered in the integration process of AI and blockchain, and to protect user privacy and trust.

While both technologies have the potential to reshape the very foundations of society, public awareness of them is currently low. If the benefits, risks and precautions of the combination of AI and blockchain technology can be popularized to the public, it will make everyone more confident in the combination of blockchain and AI technology and improve user demand.

Once more people see the synergy between decentralized systems and AI technology, more AI systems will integrate encryption security mechanisms and blockchain applications. This will effectively solve the problem of user trust, allow them to interact with AI more confidently, and promote the sustainable development of AI technology.

The Future of AI and Blockchain

The advantage of AI is large-scale intelligence, while the advantage of Web3 is large-scale coordination, value exchange and trust minimization. So when the two are combined, it will open the door to a new world, bringing higher security, transparency and efficiency to many industries.

The combination of AI and blockchain will have a huge disruptive impact on various industries. As more and more companies begin to use AI-integrated software to automate workflow, improve efficiency and optimize business, AI models will continue to enter more market segments.

At the same time, as public trust in institutions has waned in recent decades, users have also increasingly opted for apps with encryption guarantees. The convergence of these two paradigm shifts is poised to reshape the way societies and economies function.