Taking it to the next level. In his recent post, he shared the concept of “infofinances,” which combine information and finance via blockchain, going beyond traditional prediction markets.
Buterin sees huge potential in prediction markets, considering them not just a betting tool, but also an alternative source of information. He emphasized that Polymarket and similar platforms often provide more accurate and useful information than traditional media. As an example, he noted Polymarket’s successful prediction of Donald Trump’s election chances when the mainstream media presented different data.
In his view, prediction markets create an innovative model of news and finance — “infofinances” — that can increase trust and accuracy of information by using blockchain to increase transparency. “Some associate forecasting only with elections, viewing betting as a game of chance,” Buterin writes, “but it’s much deeper than that. The real value of such markets lies in their ability to highlight key information and offer participants a new format of engagement.”
Buterin explains that “infofinance” allows for the formation of a kind of three-sided market. In this model, participants create forecasts, users analyze them, and the system provides publicly available data, creating a mechanism for collecting reliable information. In such an ecosystem, financial interests are synchronized with the transfer of quality information, forming a sustainable, value-oriented structure.
“Over the next decade, one of the key drivers of infofinance development will be artificial intelligence,” Buterin added. “Technologies such as LLM and others will allow the creation of millions of mini-markets for ‘micro’ decisions, which will make the decision-making process more accurate and detail-oriented.”
Buterin believes that the concept of “infofinance” has the potential to expand beyond prediction markets to areas such as decentralized autonomous organizations (DAOs), personal tokens, and advertising. For example, in a DAO, prediction markets could be used instead of voting, combining participant predictions and AI to improve governance decisions.