AI is transforming business and government.
Blockchain brings transparency and ownership.
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Decentralized infrastructure can compete with huge data centers.
Artificial intelligence (AI) is rapidly transforming entire industries. However, its significant potential also creates risks. AI models under the control of a few corporations can exacerbate existing inequalities while cementing the power of big tech companies.
To tackle these issues, some companies are leveraging the potential blockchain technology. DailyCoin spoke to Mario Casiraghi, Co-Founder of Singularity Finance, a company working at the intersection of these technologies. He explained how blockchain tech can democratize control and ownership over AI.
The Potential of The AI Economy
“The potential of an AI-driven economy is absolutely immense, and we’ve only started to scratch the surface,” Mario Casiraghi, Co-Founder of Singularity Finance, enthused in an interview with DailyCoin. AI is transforming both industries and governments, he explains. “We can see countries like Bahrain leading the charge by integrating both AI and blockchain to create more efficient governance structures.”
To the Singularity Finance Co-Founder, AI is also driving financial inclusion, with smaller traders benefiting as much as big ones. “For the first time in history, anyone with an internet connection can access AI-driven financial tools,” he explained. “Those who are not fully financially literate, or just don’t have the time, can also benefit from AI-driven portfolios, complete with personalization from a robo-advisor,” he added.
Still, AI also creates new challenges, especially when it comes to inclusion. “We have to be very careful that this new technology doesn’t inadvertently end up creating more inequality,” Casiraghi warns. People with no access to the technology or the skills to use it may be left behind.
There are also issues with the ownership and transparency of data used to train AI models. AI relies on vast datasets, which raises questions about privacy. Moreover, there is always a risk of bias in the models. These are issues that blockchain technology can fix, Casiraghi explains.
AI’s Role in DeFi and Risk Management
Casiraghi also explained the role of AI in trading, especially for decentralized finance (DeFi). The predictive capabilities of AI can make markets more efficient, and enable investors to manage risks more effectively. “AI can predict potential risks by identifying patterns that may be missed by traditional methods,” Casiraghi elaborated.
What is more, AI has the advantage when it comes to speed and adaptability. For instance, AI can “give real-time insights and have adaptive learning capabilities,” he explained. Unlike traditional systems, which rely on static models, AI introduces a dynamic element in trading. AI can simulate a large wide range of outcomes based on real-time data quickly. This leads to faster and more accurate decision-making.
What is more, AI also tackles human biases in trading. Casiraghi noted, “Human biases often influence outcomes in traditional risk management systems. AI models, in contrast, provide objectivity and continuous improvement through feedback loops.”
Blockchain’s Potential in the AI Economy
Currently, the ownership of the model and its data is in the hands of a few tech giants. Microsoft, with its investment in OpenAI, and Google with Gemini are the biggest players in the field. Casiraghi explains how blockchain can change the game.
Singularity Finance, an EVM-compatible Layer-2 blockchain focuses on putting all AI resources on the chain. “We’re tokenizing the entire AI value chain,” explains Casiraghi. “Apps, models, datasets, and AI services will be accessible as assets to all.”
This is also giving a competitive edge to smaller companies. “We’re giving smaller companies a fighting chance against the giants,” He explains. By making AI models, datasets, and services accessible as tokenized assets, startups can compete without the need for massive capital expenditures. This also goes for AI’s significant infrastructure demands.
How Decentralization Can Compete With Data Centers
AI has significant demands when it comes to computational resources and energy, stressing existing infrastructure. This is why big tech companies like Google have turned to nuclear power to fuel the growing energy demands of AI.
Casiraghi suggests that “some estimates suggest that the power needs of data centers could triple by the end of the decade, which is a massive challenge for existing infrastructure”. What is more, securing energy for new data centers is slow, and can take years, he added. With AI moving fast, delays like these are untenable, revealing the need for alternatives.
Decentralized frameworks were designed to tackle these challenges years ago,” Casiraghi notes. By distributing workloads and using decentralized cloud computing, they offer a faster route to expansion. This is necessary to keep up with the rapid growth of AI, Casiraghi highlights.
Importance of Layer 2 Solutions in AI
While infrastructure is a major bottleneck for centralized AI, blockchain scalability is a bottleneck for decentralized AI. The largest blockchain networks can’t handle the significant amount of data that AI needs to work. For this reason, Layer 2 solutions are essential, Casiraghi explains.
“L2s are going to be necessary because AI will need to process huge amounts of data, and it’ll need to do so very quickly and efficiently,” Casiraghi noted that these solutions are essential to reduce costs, as well as make the decentralized AI models operate faster.
“Off-chain transactions reduce congestion on mainnets and allow for fast AI-driven decision-making,” Casiraghi added. He concluded that Singularity Finance’s EMV-compatible Layer 2 network is designed with that in mind.
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