Blockchain, AI & the Future of Automation
How Blockchain is Utilizing AI Technology
Whether you are new to blockchain technology or you have experience working in this space, innovation has grown exponentially in the last ten years. Although the concept of ‘distributed ledger technology’ has been around for quite some time, it was the consensus protocol that was key in the creation of Bitcoin and allowing for the boom in blockchain technology innovation. Bitcoin began trading in 2010 and has proven to be an effective decentralized digital currency operating on a peer-to-peer network without a central authority. Although the price can be volatile, it has gained acceptance as a secure decentralized digital currency. In 2013, we saw the creation of the Ethereum blockchain which brought a decentralized platform that supports the use of smart contracts.
One of the key innovations that has arisen from Ethereum’s decentralized application protocol is the concept of Automated Market Makers (AMMs). Traditional finance has always relied on a centralized counterparty or custodian to hold client funds and to ensure settlement of any trades made. In 2018, a new decentralized application called Uniswap began offering investors a way of transacting in a non-custodial way. By using a smart contract, an investor is able to trade one token for another token without needing a centralized counterparty for settlement. Uniswap has since become the largest decentralized exchange with upwards of $1.7 Bio in daily turnover in 2023. The application uses an AMM in order to provide liquidity.
In five years, we have seen enormous growth in trustless services and applications such as Uniswap that allow businesses and individuals to operate in a decentralized way. The innovation in this space is moving at breakneck speed and we would expect to see these decentralized applications continue to change how we work and how we play.
In 2023 a key term that we are hearing more of is artificial intelligence. This is in part thanks to the recent success of ChatGBT, which is getting headlines for its ability to share information in a way that would appear to be written by a human. This type of technology is not new, but earlier versions left much to be desired whereas the technology now appears to be significantly more useful. On the other hand, this has sparked concerns for schools in how they patrol plagiarism and has sparked concerns for journalists who worry that this technology could take over their jobs. We have also seen similar strides made in other areas of programming, art, and design.
Looking at the blockchain space, we have seen similar hype in a number of applications that solve problems using artificial intelligence. Companies like Fetch.ai offer decentralized access to AI services at scale and we have seen significant investments in this space. Fetch tokens (FET) were up 500% for the year by early February. Although the advances made in AI have meant that there are more use cases for this technology, training AI on the data remains computationally intensive. Centralized organizations such as Amazon Web Services offer similar AI services and can do so as part of a greater cloud services offering (which many users of AI require). Applications such as Fetch AI are able to share access to computational power that might not otherwise be used, allowing these services to be more environmentally friendly and maximizing the efficiency of this computational power. Creating decentralized applications that offer computational bandwidth for AI highlights how versatile blockchain technology can be.
When we look at the uses of artificial intelligence and machine learning (for clarity, we consider machine learning to be a subset of AI and a more applicable name for training large data sets to make predictive output) we believe that the blockchain is a goldmine in itself. Blockchains are unique in that the vast majority of transactions are public. Using open-source data, we can see the transaction happen in real time and the key metrics of the markets, we can look at individual wallets and what they hold, and we can generally see an unlimited data perspective on the microstructure of the market.
At Grantfin, our focus is to bring out these significant data points to better understand blockchain data and the market structure. Seeing and analyzing these key data metrics of automated exchanges and using machine learning to create transparency on key market trends and opportunities is the main goal. We then use this data to better understand how investors can access high yields that are offered in DEX liquidity pools while using predictive analytics to risk-manage these positions.
At Grantfin, we believe there is enormous potential in using the power of machine learning to decode crucial trends in blockchain applications. We believe that understanding and interpreting the enormous amount of data that the blockchains create will allow us to better locate investment opportunities in Defi as well as develop a strong risk management strategy. Looking at the potential size of this market, in 2020 the total value locked (TVL) in crypto was around $1 Bio. The TVL is now currently at $50 Bio, but expectations by key analysts are calling for the TVL to reach $500 Bio by 2025. Grantfin believes that using machine learning to better understand market dynamics, to find value opportunities onchain, and to risk-manage using these key predictive analytics is groundbreaking and we are excited by what we have already achieved and what we believe we can do in this space.
