Blockchain’s potential: How AI can change the decentralized ledger
Artificial intelligence’s transformative power in relation to blockchain technology is being severely overlooked, say experts.
One reason is that blockchain’s use of a decentralized ledger offers insight into the workings of AI systems and the provenance of the data these platforms may be using. As a result, transactions can be facilitated with a high level of trust while maintaining solid data integrity. Not only that, but the use of blockchain systems to store and distribute AI-centric operational models can help in the creation of an audit trail, which in turn allows for enhanced data security.
Furthermore, the combination of AI and blockchain, at least on paper, seems to be extremely potent, one that is capable of improving virtually every industry within which it is implemented. For example, the combination has the potential to enhance today’s existing food supply chain logistics, healthcare record-sharing ecosystems, media royalty distribution platforms and financial security systems.
That said, while there are a lot of projects out there touting the use of these technologies, what benefits do they realistically offer, especially since many AI experts believe that the technology is still in its relative infancy? There are many firms that are marketing the use of AI as part of their current offerings, giving rise to the blatant question: What exactly is going on here?
With the cryptocurrency market continuing to grow from strength to strength over the last couple of years, the idea of artificial intelligence (AI) making its way into the realm of crypto/blockchain technology has continued to garner an increasing amount of mainstream interest across the globe.
Are AI and blockchain a good match?
To gain a broader and deeper understanding of the subject, Cointelegraph spoke with Arunkumar Krishnakumar, chief growth officer at Bullieverse — an open-world 3D metaverse gaming platform that utilizes aspects of AI tech. In his opinion, both blockchain and AI address different aspects of a dataset’s overall lifecycle.
While blockchain primarily deals with things like data integrity and immutability — making sure that information data that sits on a blockchain is of high quality — AI uses data that is stored efficiently to provide meaningful and timely insights that researchers, analysts and developers can act on. Krishnakumar added:
“AI can help us to not just make the right decisions through a specific situation, but it can also provide predictive heads-up as it gets more trained and intelligent. However, blockchain as a framework is quite capable of being an information highway, provided scalability and throughput aspects are addressed as this technology matures.”
When asked whether AI is too nascent a technology to have any sort of impact on the real world, he stated that like most tech paradigms including AI, quantum computing and even blockchain, these ideas are still in their early stages of adoption. He likened the situation to the Web2 boom of the 90s, where people are only now beginning to realize the need for high-quality data to train an engine.
Furthermore, he highlighted that there are already several everyday use cases for AI that most people take for granted in their everyday lives. “We have AI algorithms that talk to us on our phones and home automation systems that track social sentiment, predict cyberattacks, etc.,” Krishnakumar stated.
Ahmed Ismail, CEO and president of Fluid — an AI quant-based financial platform — pointed out that there are many instances of AI benefitting blockchain. A perfect example of this combination, per Ismail, are crypto liquidity aggregators that use a subset of AI and machine learning to conduct deep data analysis, provide price predictions and offer optimized trading strategies to identify current/future market phenomena, adding:
“The combination can help users capitalize on the best opportunities. What this really translates into is an ultra-low latency and ultra-low-cost solution to fragmented liquidity — a multitrillion-dollar problem that plagues the virtual assets market today.”
On a more holistic note, Ismail pointed out that every technology has to go through a cycle of evolution and maturity. To this point, he highlighted that even when the banking and finance sectors began adopting digital assets, there were major concerns across the board about whether these assets had progressed enough to be successfully implemented. “AI and its subsets bring tremendous advantages to the crypto industry but should be ethically promoted with a long-term vision at its core,” he closed out by saying.
More work may be needed
According to Humayun Sheikh, CEO of Fetch.ai — a blockchain project aimed at introducing AI to the cryptocurrency economy — as Web3 and blockchain technologies move forward, AI will be a crucial element required to bring new value to businesses, adding:
“Decentralized AI can remove intermediaries in today’s digital economy and connect businesses to consumers directly. It can also provide access to large volumes of data from within and outside of the organization, which when analyzed using AI scale can provide more actionable insights, manage data usage and model sharing, and create a trustworthy and transparent data economy.”
In terms of the gap that exists between AI and its apparent lack of use cases, Sheikh believes that the dichotomy does not hold true since there are already many use cases for everyone to see. Fetch.ai, for example, has been building systems for deploying AI and blockchain within supply chain ecosystems, parking automation frameworks, decentralized finance (DeFi) and more. Fetch is also planning on releasing consumer-friendly AI applications starting in the United States in the near term.
However, Krishnakumar believes that more needs to be done when it comes to making AI more data efficient so as to really serve the world at scale. To this point, he noted that with the advent of quantum computing, AI could scale heights like never seen before, adding:
“This can, for instance, bring down the time taken for drug discovery from 12 years to a couple of years could be on the cards. Modeling nitrogen fixation and industrializing it to reduce carbon emissions in fertilizer factories is another example. Modeling protein folding and providing customized medication for cancer is another use case that could be achieved.”
Does blockchain need AI to succeed?
Chung Dao, CEO and co-founder of Oraichain — a smart contract and decentralized app platform — believes that blockchain technology is more than what most people like to believe it is, which is a closed world of financial transactions without any connection to real-world assets and events. He told Cointelegraph:
“AI must come to help blockchain recognize real world utility, expand its applicability and enable intelligent decision-making. Both technologies are in their early stages, but not ‘very early.’ There are many successful AI solutions that recognize patterns better than humans, and there are no doubt many advantages of automation in a wide range of businesses.”
Dao noted that there’s already a robust infrastructure for AI ready to be implemented atop existing blockchain technologies, one that can enhance “trust, identification and decentralization” across the space. In this regard, Oraichain has a whole ecosystem dedicated to this: The project utilizes an oracle mechanism that integrates AI into smart contracts as well as harnessing the power of an AI-centric data management system and marketplace.
Therefore, as we move into a future driven by the principles of decentralization, it stands to reason that futuristic technologies such as artificial intelligence will continue to gain more ground within the global crypto landscape over the coming months and years.