Original Author: Deep Tide TechFlow

Tomorrow, the long-awaited $BIO will officially launch. As a DeSci project personally backed by Binance, the market is speculating whether the launch of $BIO will drive a chain bull market in the DeSci sector and siphon off some liquidity from the AI sector.

But are the AI and DeSci sectors necessarily in competition? Not at all. The recently discussed Solana-based project YesNoError has carved out a path that integrates DeSci with AI, using AI technology to review and identify errors in scientific papers.

Its token $YNE reached a market cap of $60 million on the day of its launch on December 20, and was further promoted by well-known Twitter KOL Andrew Kang (hereafter referred to as AK), with a current market cap of around $50 million.

Is AI Review of Scientific Papers Really Necessary?

If you are still unclear about the practicality of YesNoError, a tweet from team member Ben Parr illustrates the necessity of reviewing erroneous information in scientific papers with an example:

In October 2024, a research paper claimed that black plastic kitchenware contained toxins, and this news quickly spread through the media. The Atlantic even published an article titled "Throw Away Your Black Plastic Kitchenware," causing public panic. Even Ben Parr himself began to clean out his kitchenware. However, Joe Schwartz, the director of the Science and Society Office at McGill University, discovered a significant mathematical error in the study—a simple multiplication mistake that led to a reported toxicity level ten times higher than the actual level. This case shows that even seemingly authoritative research can contain significant errors, which can have substantial impacts on the lives of ordinary people.

Using AI technology to review research papers can minimize these basic numerical calculation errors. YesNoError was born out of this need.

YesNoError was created by Matt Schlicht and uses OpenAI's o1 model as its technical foundation. The project operates straightforwardly: the team uses AI to review research papers and then publicly publishes the identified issues on their website yesnoerror.com and official Twitter.

This transparent operation allows both the scientific community and the public to be promptly informed of potential issues in important research. Although the project has only just begun, it has already achieved some significant results, identifying several errors in research.

The token $YNE is also given a practical use case, allowing holders to spend $YNE for priority reviews of their papers by YesNoError AI.

As of now, YesNoError AI has reviewed 2,219 papers and indeed found numerous errors in them.

Recognition or Doubt: Voices in the Market

AK Optimistic, Promoting the Project

On the day of the $YNE token launch, AK, who has always been optimistic about DeSci, expressed his appreciation for the YesNoError project.

AK stated, "The core value of YesNoError lies in the real implementation of cryptocurrency x AI x DeSci."

YesNoError leverages the characteristics of the cryptocurrency ecosystem, where capital does not require traditional investment returns. As long as you can attract enough attention, you can secure ample funding. (This is the attention economy; if people pay attention, they will buy tokens.)

At the same time, YesNoError has found a great application direction for cryptocurrency. In the right context, tokens are no longer just air but can indeed support public goods that are difficult to maintain under traditional business models.

Perhaps due to his strong belief (or significant holdings?), on December 31, AK published another article introducing and praising the necessity and practicality of YesNoError from a data perspective.

AK claimed that YesNoError has the capability to review errors in over 90 million papers in the global scientific literature database, which can be completed in just a few weeks or months. In contrast, manual review would take tens of thousands of years, even if a team of 5,000 PhDs were assembled, it would still take nearly a decade (and during that decade, they would not be able to keep up with the speed of new paper publications), with a conservative estimate of needing $5.4 billion.

Through an optimized AI model, the review can be completed for about $30 million (at $0.30 per paper), achieving a more accurate and standardized review process—costing less than 1% of the manual method.

In traditional scientific fields, raising $30 million is no small feat, but it is evidently much easier in the crypto space. (Although it includes many speculative factors, the market cap of $YNE has already reached $50 million in just ten days.)

Currently, the AI agent has reviewed over 1,700 papers, with an error rate of around 3-4%. As it continues to optimize, its processing speed will further improve. Among the 90 million papers, there are likely many important papers containing significant errors, and correcting these errors could have a substantial positive impact on the world.

The official account of BIO Protocol also agrees with AK's view:

Is It a False Demand? Different Voices

Beyond the optimistic voices, some have questioned the real necessity of YesNoError.

Kyle Samani, co-founder of Multicoin Capital, raised objections under AK's promotional post:

Kyle believes that according to the 80/20 principle, only a few papers are truly important, and these important papers are unlikely to contain known errors due to the attention they receive.

However, Andrew Kang countered with data. He pointed out that even according to Kyle's logic, among 90 million papers, assuming only 5% are important, that still amounts to 4.5 million important papers. Even if only 0.1% of these important papers have errors, it still means there are 4,500 important papers that need correction. The previously mentioned "black shovel research" case fully illustrates that even impactful papers can contain errors that affect society.

Conclusion

The idea of AI reviewing papers is not new; there have been many use cases since the advent of ChatGPT. In the crypto space, the emergence of YesNoError may not only address the issue of errors in scientific papers but also lead to some genuine developments in the use cases of cryptocurrency beyond speculation (though it may still be in the early stages, and some value still depends on market speculation).

Returning to market behavior, while many optimistic actions in the market can be summarized as "the butt decides the brain," if a project is genuinely feasible and has practical value beyond speculation, then this behavior of "making money while standing" will likely be recognized by the market.

How YesNoError develops in the future will depend on the project's determination to continue after the speculative hype subsides. We will keep an eye on it.

May there be more projects that benefit the world.

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