Blockchain

AI and Blockchain Converge: Conflux’s Roadmap to a Smarter, More Productive Web3

AI and Blockchain

Artificial Intelligence (AI) is evolving rapidly, but currently, the technology is mainly centralized, which is recognized as problematic by many people working within the Web3 community for several reasons. The most successful AI companies today, like OpenAI, might have “open” in their names, but ironically, they’re anything but open. These few companies control the resources, the data, and the models, leaving most of the world dependent on their technologies.

Centralization is precisely what blockchain technology was designed to circumvent. Decentralization is designed to empower individuals, distribute control, and ensure transparency through the nature of blockchain technology. But when it comes to AI, there are some significant technological challenges we must first surpass.

I believe decentralized AI is the future of this technology. Blockchain has unique qualities that could benefit AI, like its consensus mechanisms and its potential for scientific decision-making. This isn’t just an ideological concept—it’s something that we’re actively building at Conflux Network. We’re innovating to create foundations for resolving some of the challenges in the future, and introducing AI functionality to our blockchain infrastructure.

The Challenges of Decentralized AI

One of the largest challenges in creating decentralized AI is the cost and complexity of training models. AI training requires vast computational power, which is currently only available to a few large organizations with access to the funds and resources required to run this activity. If training AI were inexpensive, companies like NVIDIA wouldn’t be as valuable as they are to the AI industry. The reality is that decentralizing the process of training LLMs amplifies these demands. The resources would be massively increased compared to the resources required for this same task in centralized systems.

Another challenge is that AI needs massive datasets to function effectively, and blockchain, in its current form, is not designed to handle that scale. Storing data on a blockchain is expensive because every node in the network needs to store and process the same data. This is a significant limitation for blockchain-based AI, and overcoming it requires rethinking how data is managed within a decentralized system.

Conflux’s Proof of Useful Work: A Step Toward Decentralized AI

We have begun to move beyond traditional Proof of Work (PoW) consensus mechanisms, which use computational power to solve cryptographic puzzles. Instead, we’ve developed Proof of Useful Work (PoUW), a new approach that redefines the traditional PoW model, aligning it with meaningful computations that benefit society and enhance productivity, like AI inference and scientific research.

PoUW aligns the blockchain’s security mechanism with meaningful, productive tasks. In essence, the energy spent securing the blockchain also goes toward solving valuable AI problems. This is a major shift from how PoW has traditionally been used, and it opens up new possibilities for how decentralized networks can contribute to AI development.

We’re focusing on highly parallelizable problems, like AI inference and protein prediction because these tasks are well-suited for decentralized networks. They can be broken down into smaller tasks and distributed across the network, allowing multiple nodes to contribute to the exact computation. The result is a system where blockchain miners are no longer just securing the network but actively contributing to AI research and development.

Also read: 7 Best Web3 Domain Name Registry Platforms

AI-Integrated Virtual Machine: Unlocking Smarter Contracts

Another critical innovation we’re introducing at Conflux is the AI-Integrated Virtual Machine (VM). This enables basic AI operations to be integrated directly into smart contracts, allowing for more complex and responsive decentralized applications. Imagine a smart contract that can interact with real-time AI models, make decisions based on machine learning may even automate entire processes using AI-driven logic. With this integration, the possibilities for decentralized AI applications are endless.

The AI-integrated VM also allows for asynchronous task dispatch, meaning that tasks can be assigned to nodes across the network, and the results can be claimed once completed. This opens up a new realm of functionality for decentralized applications, enabling them to leverage AI computations without relying on centralized infrastructure.

Reusing Computational Power for AI and Consensus

We are currently exploring ways to reuse computational power between AI and consensus mechanisms. This is one of the most exciting aspects of our AI roadmap because it allows the same resources that secure the blockchain to also fuel AI development. By doing this, we’re effectively doubling the value of every computation performed on our network. It’s a win-win: the blockchain becomes more secure, and AI development becomes more efficient.

We’re extending this approach to side-chains, decentralized Layer 2 sequencers, and other blockchain infrastructures. This not only enhances security across the ecosystem but also enables scalable AI computations that can operate seamlessly within the decentralized environment.

Why These Innovations Matter

The reason these innovations are so important is that they solve some of the core challenges in decentralizing AI. By integrating AI into the blockchain, we’re creating an environment where training and running AI models without relying on a few large companies or centralized systems could be possible. This opens up AI development to a much broader group of people and organizations, ensuring that the future of AI is more transparent, accessible, and fair.

At the same time, we’re addressing the inefficiencies of storing data on the blockchain and making AI computations more cost-effective by reusing resources between consensus and computation. These steps are crucial in building a decentralized AI future where innovation is driven by a global Web3 community rather than a handful of corporations. As AI continues to evolve, decentralization will be vital to ensuring that this powerful technology benefits society.

Written by
Dr Fan Long

Dr Fan Long is the Founder of the Conflux Network and the Shanghai Tree-Graph Blockchain Research Institute. He graduated from Tsinghua University Yao Class and gained a PhD in Computer Science from MIT, where he received the MIT Best Dissertation Award. He is also a recipient of the ACM SIGSOFT Outstanding Dissertation Award. Fan has been published in over 20 renowned computer science conferences with more than 1000 citations. His research interests include systems security, programming language, and blockchain. As a competitive programmer, he has also won Gold medals twice in the International Olympiad of Informatics (2005, 2006) and the ACM-ICPC Program Contest regional championship.

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