Decentralized Finance (DeFi) saw its rise back in the summer of 2020. If you’re a crypto native, you’ll remember this as “DeFi Summer”. This was the DeFi equivalent of the dotcom bubble where the space saw its sharpest rise before declining significantly in recent years.
By most standards, we measure the success and activity of DeFi through a metric called TVL which stands for Total Value Locked. This measures the amount of money locked into smart contracts at any given time. At its peak, TVL hit $177 billion in 2021. Since then, the DeFi ecosystem has fizzled to $38 billion as of the time of writing.
The current state of DeFi is undeniably bad. So why did the promise of DeFi fade so fast and why has everyone left?
The Limitations of DeFi
Although an incredible breakthrough in modern finance, DeFi comes with many limitations that severely limit long-term adoption and user experience. Some of DeFi’s main limitations are:
- Transactional inefficiencies leading to high costs to users
- Complex user experience
- Concerns around smart contract security and exploits
This is part of the reason why the hype could only last so long. Onboarding new users is incredibly difficult, particularly in the current economic climate, and justifying the use of DeFi tools over traditional financial infrastructure just isn’t possible.
Will DeFi end as soon as it started?
Despite its limitations, crypto natives have grown used to DeFi and still enjoy the benefits of this new financial infrastructure on a daily basis. However, crypto natives don’t make up a big enough market to make DeFi viable, despite the space growing to over 6.5 million as of January 2023. If we’re ever to see DeFi claw its way back to all time highs and become the new norm in our global financial system, these challenges need solving.
The Power of AI in Addressing DeFi Limitations
The fusion of AI and DeFi has the potential to redefine the very foundation of web3 finance. With pattern recognition, predictive analytics, and automation capabilities, AI can mitigate the current limitations faced by the DeFi ecosystem. If we do it right, AI could be the key to unlocking DeFi’s full potential and replacing our traditional financial system with a more streamlined and reliable one.
Let’s dive into some of the ways AI can help revive the world of DeFi and bring it into mainstream finance.
Streamlining Transactions
The majority of modern DeFi platforms are built on the Ethereum blockchain. Despite the growth of layer-2 solutions on Ethereum and increased efficiency upgrades, the same old problems remain. Transactions are too slow and expensive. For context, the Ethereum blockchain currently handles around 30 transactions per second. In contrast, the Visa network handles around 1,700 transactions per second. The more transactional demand a blockchain has, the more expensive it gets. This is bad for users.
AI can play a big role in streamlining transactions by learning from historical transactional data and analyzing past congestion and fees to start building predictive patterns. Using this data, AI models could, in theory, create optimal transaction predictions as well as suggest resource allocation strategies for the underlying blockchain networks that modern DeFi platforms rely on. This would be a big step towards making DeFi a viable financial infrastructure for the future.
Elevating the User Experience
For many, including crypto natives, the web3 experience is overwhelming, at best. It takes a long time to get comfortable and familiar with all the different applications out there. Due to its decentralized nature, this is an inherent flaw of DeFi. Contrast that to using a modern fintech tool such as Stripe or Wise and you’ll quickly see why the current state of DeFi isn’t good enough for mass adoption.
An AI model could aggregate data across blockchains and help us build personalized user experiences, guiding users based on their past behaviors or based on the current trends. This would lead to much less time fumbling through complex interfaces and more time making informed financial decisions. In order to leverage the power of DeFi, we need a cleaner user experience.
Fortifying the Landscape
Security is arguably one of the top priorities in any financial system. The last thing you want is to make a wrong turn and lose all your money. In the traditional financial system, we’ve become accustomed to assurances that our money will never be lost when custody is held by a centralized bank. Those assurances are the tradeoff we make when we engage in a globally decentralized financial system. Most people are not going to accept that tradeoff. Well that’s where AI can help.
An AI model thrives on data. By feeding a tailored AI model historical data on transactions, frauds, and security breaches in web3, it can use this to create automated alerts for users warning them of potential threats. As the model gets better, it could foresee vulnerabilities with a DeFi platform, informing both active users to be wary and the platform developers that they need to strengthen security.
These are just some of the ways that we can leverage AI to make DeFi a safe, efficient, and thriving financial ecosystem for the entire world. The problem is, we’re not quite there yet.
The State of AI Models
The allure of Artificial General Intelligence (AGI) causes most data scientists and researchers to focus their efforts on this moonshot task. Although we’ve seen remarkable advancements in these models, take ChatGPT for example, we could be spending resources in a far more efficient way to address more niche challenges. But talent gravitates to the space where there are rewards to reap. We need to incentivize more rewards for specific use cases that might otherwise fly under the radar, such as DeFi.
That’s why we’re building bitgrit, a marketplace for AI models that’s powered by web3 financial infrastructure. We’re committed to making AI more accessible for all by increasing the number and quality of AI models available on the market. We do this by orchestrating dynamic competitions that foster the development and birth of cutting edge AI models in the sectors that need it most. Additionally, this allows data scientists and AI researchers to get financially rewarded for contributing to the space, making it a viable place to apply their skills.
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