AI-Enabled Cross-Chain Interoperability: Unifying DeFi

Our previous entries into our AI series have demonstrated that technology is poised to undergo the next great industrial revolution since data has become the most valuable asset on earth. Then we unpacked the multifaceted challenges that AI must overcome and how the concentration of data silos in Web2 is hindering the development of open-sourced AI protocols.

Web3 and the development of interoperable blockchains with shared, immutable data could disrupt these centralized Web2 data silos. Yet, the issue of blockchain interoperability and the frictionless movement of digital assets across chains has been one of developers' most arduous and elusive goals to date.

In this post, we will examine whether the integration of AI will be the missing piece that unifies these isolated interoperable protocols and sends DeFi development into the stratosphere or if it will be yet another incomplete solution that creates more issues as it solves them.

Recreating Web2 Data Silos

Blockchain technology has repeatedly demonstrated its utility in both the real and digital worlds. It has been used in everything from powering the future of finance to real-world supply chain management and healthcare. Utilizing a decentralized, immutable ledger technology has proven to be a potent piece of technology in the right hands.

Unfortunately, despite its decentralized foundations, the blockchain industry suffers from the developmental issue of siloed protocols that remain fractionalized and separated. This may sound similar to the mergers and acquisitions period in the last twenty years, where tech and data were consolidated into the hands of only a few web2 tech behemoths.

Yet, there are important differences between the two. One significant difference between blockchains and Web2 data silos is that the siloed nature of open protocols is due to a technological impasse rather than any centralized corporate directive. Most blockchains are, by default, open-sourced, and the cross-chain integration issue is because they simply can’t consolidate fundamentally different coding languages, consensus mechanisms, and blockchain architecture.

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Ironically, the revolutionary foundation of the technology and how layer one blockchains are designed is what makes them so difficult to consolidate into a single interoperable solution. This disconnect and lack of communication between protocols is an issue because it creates limitations and a friction point for users. The difficulty in moving digital assets across chains is not trivial.

Another significant reason why it is important to solve the interoperability issue within the blockchain industry is this fear of centralization. Without interoperability, every dApp, token, and protocol will eventually migrate to a single layer one blockchain, creating a central point of failure. Currently, Ethereum makes up more than 55% of the total value locked across the entire DeFi industry.

Ethereum excelled through its first-mover advantage, and while solidity remains the preferred language for developers, the dominance of its TVL across DeFi should give us pause. When Ethereum moved from a proof-of-work (PoW) to a proof-of-stake (PoS) consensus mechanism during The Merge, it lost a degree of decentralization and became more prone to node consolidation and attacks. Integrating interoperability solutions could help reduce this risk by redistributing the concentration of TVL across multiple chains.

The Current State of Layer Zero Interoperable Blockchain Solutions

The concept of interoperable blockchains is certainly nothing new. Since Bitcoin first burst onto the scene in 2009, users have consistently sought ways to leverage its value. The rise of the multichain era and smart contracts introduced the tools that allowed developers to experiment with side chains and set the foundations for modern-day DeFi. Yet, the multichain era will only succeed if the assets and information within each blockchain can move seamlessly between chains. This has given rise to novel interoperable solutions like the Cosmos and Polkadot networks.

In 2014, Jae Kwon and Ethan Buchman co-founded the Cosmos network. They developed the Tendermint PoS consensus mechanism before fully releasing the software in 2019. The network was one of the first global interoperable chains, touting itself as the “Internet of Blockchains.” Cosmos’s success hinges on its Inter-Blockchain Communication Protocol (IBC). It is an open-sourced standardized protocol that handles the authentication and transport of information and assets across chains.

Shortly after the release of the Cosmos network, Peter Czaban and Ethereum co-founder Gavin Wood released Polkadot in 2020. Considered one of the most successful blockchain scaling protocols, Polkadot leverages its community of $DOT holders to make governance decisions and decide which chains to integrate into the Polkadot ecosystem. The protocol uses a series of relaychains and parachains to integrate the transactions across multiple chains. It defines itself as a network of networks.

The current state of interoperable blockchains is ever-evolving as more chains begin to be integrated into layer zero blockchain networks like Polkadot and Cosmos. While this is an exciting area of the blockchain industry, it is still littered with pitfalls and challenges.

Enhancing the Interoperability of Blockchains

In our earlier articles, we demonstrated the sheer power that general-purpose machine-learning (ML) models can have on data analysis and predictive modeling. In our first entry, we explored how Google’s Deepmind Alphafold leveraged these models in protein-folding genetic exploration and development. The result was that AI could accelerate the discovery of gene proteins and predictively map treatment.

The same technology that enables the hyperanalysis of mass data in the human genome can be directly applied across interoperable blockchains and DeFi. By analyzing the massive amounts of transactions that occur on multiple blockchains simultaneously, AI could better identify trends, more efficiently route blocks, and stop malicious actors from siphoning attacks before they happen.

We saw in our Revolutionizing DeFi piece how DeFi has historically been prone to targeted hacks. Bridges between chains can create an attack vector for malicious actors, and as a result, the layer zero chain is only as secure as its weakest bridge. AI can help solve this issue by continually auditing the code, screening for potential hacks in real-time, and enhancing the overall security of the interconnected chains.

Is AI Blockchain Interoperability Integration a Poison Bullet?

Our previous entries have shown the roadblocks to such AI development. When we explored the Limitations to a Technological Revolution, the issue of poisoned and manipulated data became clear. Just as AI can be utilized to accelerate and enhance data analysis and deployment, it must also be scrutinized regarding the quality of its training data.

Could the integration and reinforced training of massive concurrent data sources pose a critical failure point? If manipulated or poisoned data is inserted at any level within any blockchain and later utilized to train an AI model, it could cause a cascading effect across every interoperably connected chain.

In 2022, the blockchain industry witnessed firsthand the frailty of algorithmic stablecoins when $UST depegged, causing the entire $60 billion Terra ecosystem to implode in a matter of days. Hallucinations within AI protocols remain a common feature. Even if the data a model is trained on is proven trustworthy, the analog weights and balances applied to each model could still result in incorrect results. This is why integrating AI protocols into interoperable blockchains could create a compounding effect across multiple chains at a pace that may surpass the Terra Luna fallout.

The Next Evolution of DeFi

DeFi, interoperable layer zero blockchains, and AI are all at the cutting edge of technology in their own right. The crossroads at which these technologies intersect has the potential to reshape the landscape in which they sit, improving the ease at which assets move and enhancing the security of each interwoven chain.

Yet, acceleration without guardrails and introducing deep learning AI protocols into an area of blockchain technology that has struggled with bridge hacks in the past may create some unexpected negative outcomes.