AI Blockchains Vs Standard Blockchains Explained

Much has been said about the potential of the convergence between artificial intelligence and blockchain, but it’s important to realise that AI can’t just use any old decentralised network. 

If we’re going to make AI more open and transparent and we must, if we don’t want it to be monopolised, controlled, made inaccessible and potentially even abused – then we’re going to need a dedicated blockchain network that possesses some unique capabilities. AI blockchains must provide a way for anyone to upload, share and monetise their data, and for AI models to be trained with full attribution, so the users who contribute are rewarded for doing so.  

Moreover, they must serve as open platforms where anyone can build AI applications that are controlled by their users, with democratic governance to ensure they’re aligned with people’s needs. General-purpose blockchains don’t quite cut it, which is why a new generation of dedicated AI blockchains like Openledger hold so much more promise. 

 

What Makes An AI Blockchain Different?

 

To understand what an AI blockchain is, we need to know what a regular blockchain is first. Most people are familiar with the biggest decentralised networks, such as Bitcoin and Ethereum and these are two prominent examples of “regular” blockchains.

In the case of Bitcoin, its blockchain was designed solely to support that cryptocurrency, keeping a list of user’s wallets, the amounts of BTC they hold, and an immutable record of every transaction that was ever made. 

Ethereum was designed to do a bit more, with its support for smart contracts enabling it to host decentralised financial applications, non-fungible tokens and real-world assets, therefore making crypto much more useful. 

AI blockchains such as Openledger, on the other hand, are designed specifically for AI applications. They serve as a foundation for training decentralised AI models, running them and keeping track of who used them, the data that was fed into them, and how this information was used. In doing this, Openledger enables “data attribution”, which is key to ensuring the data creators are rewarded for their contributions. 

Credit For Creators

 

If you build an AI model on Ethereum, you’ll quickly discover that its architecture doesn’t support data attribution. There’s no way of showing who should be credited for the data that’s used to train your model. Regular blockchains don’t allow dApps to properly credit the data they use, making attribution and rewards an impossibility. 

With AI Blockchains, these capabilities are baked into the underlying infrastructure. In the case of Openledger, it’s designed to keep a permanent record of who contributed every bit of data that was used to train one of the models it hosts. 

 

Fair Rewards Distribution 

 

This visibility is what enables AI blockchains to ensure that every participant can be fairly rewarded for their contributions. By using smart contracts, we can not only see, but also enforce compensation for data creators. Every time a model built on Openledger generates a response, it will provide visibility into how that answer was generated, showing the data that informed it, and how relevant it was. The smart contract will then automatically release a predetermined amount of “tokens”, or cryptocurrency, to the creator of that data. 

This helps to solve one of the biggest issues with secretive, centralised AI models that no offer no transparency into their training data, and have become the target of numerous lawsuits alleging copyright breaches by content creators who believe their work is being abused for profit. 

In regular blockchains, content creators cannot earn rewards. For instance, Bitcoin’s proof-of-work consensus mechanism only allows miners; the people who process transactions to earn rewards. Similarly on Ethereum, only validators, who must stake ETH tokens to participate, are eligible to earn anything. 

 

Data Security 

 

When it comes to security, regular blockchains are all about protecting funds, ensuring that transactions are secure and legitimate, preventing double spending and unauthorised access to user’s wallets. But there’s no focus on AI model safety, as they were never designed for AI in the first place. 

AI blockchains come with additional security controls in order to protect more than just transactions. Because blockchains are immutable, any AI models hosted on them cannot be tampered with or altered without everyone else knowing. They also make it possible for users to secure their data, restricting access to only those models that are willing to pay the creator appropriate compensation every time that information is used. 

Datasets uploaded to an AI blockchain can be changed by their owners, but the transparent blockchain will always keep a record of these updates, along with a full on-chain version history, so those authorised to access it can see how it has evolved, and who made those changes. In contrast, regular blockchains don’t support this kind of tracking. 

 

Value-Based Economics

  

The economics of regular and AI-focused blockchains also differ substantially, too. With regular blockchains, the economy is based on a combination of token fees (gas), the actual utility of those tokens and there is a great deal of speculative activities, with mechanisms such as staking and DeFi.

AI blockchains are a lot less speculative, with the value they provide to creators correlating to how often AI models are used. They transform AI activity into earnings for contributors. So the more often a model is used, the more revenue it generates, increasing the rewards that filter back down to the developers and data providers. This mechanism ensures that the most popular AI models generate much more value than those that are rarely used. 

 

Community-Based Development 

 

Finally, governance is a different kettle of fish too. Traditional blockchain networks get a lot of credit for making democratic governance possible, with voting systems that give more weight to those individuals who are most invested in them. By holding the network’s native token, you’re given voting rights, and the more tokens you hold, the greater the “weight” assigned to your vote. Token holders primarily vote on protocol changes and updates to the network or dApp. 

In AI blockchains, the voting mechanisms are all about the models themselves. They enable the community to vote on the features that work best and the rules for improving them, and earn rewards for participating in this process. In this way, it incentivises community participation in the process of evolving and improving AI development over time. 

 

Why Does This Matter?

 

AI blockchains have the potential to transform the AI economy and resolve longstanding issues regarding the unfairness of centralised AI models. Companies like OpenAI, Google, Microsoft, Anthropic and others are only too happy to continuously scrape the web for every bit of data they can get their hands on, in an endless quest to improve the capabilities of their models. 

But what they don’t like doing is admitting what they do. The reality is that their models wouldn’t work if they didn’t leverage the content created by other people, but they refuse to acknowledge these creators, or share in the revenues generated by their models. As a result, nobody gets paid for their contributions. 

When AI models are built on specialised blockchains, we can flip this on its head and create a more equitable economic model. AI blockchains provide full transparency over the data that’s used by each AI model.

With Openledger, every participant in the AI ecosystem generates value. It keeps a record of who provides the underlying infrastructure, such as the computing resources used. It tracks the data used to train each AI model, as well as a record of how it contributes to the model’s outputs. It also records all AI model activity, including when it was used, how it was used and who it was used by. 

This is essential to build a more equitable AI economy. After all, AI is built by humans, for humans, on human-generated data. By distributing ownership across the network and providing full attribution of who provides what, AI blockchains take back control and make sure that AI works for the people who power it. 

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