A recent report from Coinbase highlights concerns about the perceived value of various AI tokens, suggesting that their sustainability may be overstated.
David Han, a research analyst at Coinbase, pointed out that recent price surges in these tokens could be more driven by hype rather than genuine utility or usage.
Questions Arise Over the Surge in AI-Linked Crypto Projects
According to data from CoinGecko, the total value of AI-related crypto projects has reached $26 billion this year, with a notable 30% increase occurring in just one day, coinciding with the surge in Nvidia stock.
Throughout the year, tokens like Akash and Render have seen significant gains, with increases of 146% and 99%, respectively, surpassing Bitcoin’s 54% rise. Despite these impressive numbers, Han cautioned that the future prospects of many of these projects remain uncertain.
The report suggests that AI tokens often ride the wave of positive sentiment in the crypto market and AI-related news dissemination. However, Han believes that the current hype surrounding AI tokens may be inflated.
He expressed concerns that the perceived value of numerous AI tokens might be artificially inflated due to the industry’s spotlight, lacking sustainable demand drivers in the short to medium term.
Han also outlined specific challenges faced by AI tokens like Akash Network, which mirrors the operations of tech giants such as Amazon and Google by utilizing users’ computing power for cloud computing in exchange for payment. Despite increased usage, issues such as dwindling potential supply and demand for Akash Network have arisen.
Moreover, he recommended that projects like this reconsider their token distribution strategies to garner more attention, emphasizing that only “nuanced” use cases could position these projects to compete with centralized behemoths like Amazon Web Services or ChatGPT.
Buterin Supports AI Integration
In a separate development, Vitalik Buterin, the co-founder of Ethereum, recently expressed optimism about integrating artificial intelligence to address challenges within Blockchain networks.
Buterin highlighted the potential of AI-driven audits to detect and address problematic code within the Ethereum network, underscoring its role in mitigating the “biggest technical risk” to the network.
Meanwhile, Coinbase’s analysis outlines two potential growth paths within the crypto-AI sector: enhancing Blockchain data accessibility for human interpretation and analysis and decentralizing the predominantly centralized AI infrastructure. However, Han cautions that the future of decentralized AI is uncertain, citing the unpredictable trajectory of the AI industry.
