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Tomorrow, $BIO, which the market has been waiting for for a long time, will be officially launched. As a DeSci sector project personally supported by Binance, the market has speculated whether the launch of $BIO will drive the on-chain bullishness of the DeSci sector and take away some of the liquidity of the AI sector.
But are the AI and Decsi sectors necessarily competing? No. The recently discussed Solana on-chain project YesNoError has taken a path to integrate DeSci with AI, using AI technology to review and discover errors in scientific research papers.
Its token $YNE quickly reached a market value of US$60 million on the day it was launched on December 20, and was subsequently promoted repeatedly by the well-known Twitter KOL Andrew Kang (hereinafter referred to as AK). The current market value is around US$50 million.
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Is AI reviewing scientific papers really necessary?
If you still don't understand the practicality of YesNoError, a descriptive post by YesNoError team member Ben Parr illustrates the necessity of reviewing misinformation in scientific papers with examples:
In October 2024, a research paper claimed that black plastic kitchenware contained toxins, and this news quickly spread in 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 his kitchenware. However, Joe Schwartz, 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 often have substantial impacts on the lives of ordinary people.
Using AI technology to review research papers can maximize the avoidance of these basic errors in numerical calculations. YesNoError was born out of this need.
YesNoError was created by Matt Schlicht, using OpenAI's o1 model as a technical foundation. The project operates straightforwardly: the team uses AI to review research papers and then publicly releases the identified issues on their website yesnoerror.com and official Twitter.
This transparent operation allows both the scientific community and the public to be informed in a timely manner about potential issues in important research. Although the project has just started not long ago, it has already achieved some significant results by discovering several errors in research.
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The token $YNE has also been given practical applications, allowing holders to spend $YNE for priority review of their papers using YesNoError AI.
As of now, YesNoError AI has reviewed 2,219 papers and has indeed identified numerous errors in those papers.
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Approval or doubt, some voices in the market
AK is optimistic and has posted enthusiastically.
On the day the $YNE token was launched, AK, who has always been optimistic about DeSci, expressed appreciation for the YesNoError project.
AK stated, 'The core value of YesNoError lies in the genuine landing of cryptocurrency x AI x DeSci.'
YesNoError leverages the characteristics of the cryptocurrency ecosystem, where capital does not need traditional investment returns. As long as you can attract enough attention, you can obtain ample funding support. (This is the attention economy; if someone is paying attention, someone will buy tokens.)
At the same time, YesNoError has found a great application direction for cryptocurrencies. In suitable scenarios, tokens are no longer just hot air but can indeed support public goods that are difficult to maintain under traditional business models.
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Perhaps because he is really optimistic (or holds a significant amount?), on December 31, AK posted again to introduce and praised the necessity and practicality of YesNoError from a data perspective.
AK claims that YesNoError has the ability to audit errors in over 90 million papers in the global scientific literature database, which can be completed in just a few weeks or months. If done manually, it would take tens of thousands of years—even if a team of 5,000 PhDs were formed, it would take nearly ten years (and during that time, they would not be able to keep up with the publication rate of new papers), and a conservative estimate would require $5.4 billion.
The optimized AI model can complete more accurate and standardized review work for about 30 million dollars (0.3 dollars per paper)—costing less than 1% of manual methods.
In the traditional scientific industry, raising 30 million dollars is also no small feat, but obviously, in cryptocurrency, this is much easier. (Although there are many speculative factors, the market cap of $YNE has already reached 50 million dollars in just ten days.)
Currently, the AI agent has reviewed over 1,700 papers, finding an error rate of about 3-4%. Through continuous optimization, its processing speed will further improve. Among the 90 million papers, there are likely many important papers with significant errors, and correcting these errors will have a substantial positive impact on the world.
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BIO Protocol's official account also agrees with AK's view:
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Is it a false demand? Let's see the different voices.
Besides the optimistic voices, some have raised doubts about the real necessity of YesNoError.
Kyle Samani, co-founder of Multicoin Capital, expressed opposing views under AK's post.
Kyle believes that according to the 80/20 principle, only a few papers are truly important, and these important papers are less likely to contain known errors due to the attention they receive.
However, Andrew Kang refuted this 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 corrections. The previously mentioned 'black shovel research' case fully illustrates that even impactful papers may contain errors, which can have certain effects on society.
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Summary
AI reviewing papers isn't actually new; there have been many applications for AI paper review since ChatGPT was first released. In the context of the cryptocurrency industry, the emergence of YesNoError may address the issue of errors in scientific papers while also leading to some real developments in the application of cryptocurrencies beyond speculation (though it may still be in the early stages, with some value still depending on market speculation).
Returning to market behavior, although many optimistic behaviors in the market can be summarized as 'butt decides the brain,' if a project is genuinely feasible and has practical value beyond speculation, then this kind of 'standing to earn money' behavior will certainly be recognized by the market.
How YesNoError develops in the future still depends on the project's determination to continue after the market speculation subsides. We will keep an eye on it.
There are more and more projects aiming to benefit the world.
This article is authorized for reprinting from: (Shenchao TechFlow)
Original Author: Shenchao TechFlow
'Market cap reaches 50 million dollars! YesNoError relies on AI to quickly review papers; what practical functions does YNE token have?' This article was first published in 'Crypto City.'