OORT, a decentralized AI company, reached a major milestone as its image training data set climbed to the top ranks on Kaggle, Google’s popular platform for data science and machine learning.
From May 6 to May 14, OORT’s “Diverse Tools” data set appeared on the first page in key categories like General AI, Retail & Shopping, Manufacturing, and Engineering.
Although the data set has since dropped from those top stops following unrelated platform updates, the achievement shows a strong wave of community interest in high-quality, community-sourced AI data.
Unlike traditional data providers, OORT gathers training data through a decentralized, token-incentivized model that allows community members to contribute data, ensuring greater transparency, traceability, and engagement.
“The organic interest from the community, including active usage and contributions — demonstrates how decentralized, community-driven data pipelines like OORT’s can achieve rapid distribution and engagement without relying on centralized intermediaries,” said Max Li, founder and CEO of OORT.
While experts caution that Kaggle rankings don’t automatically mean enterprise adoption, they recognize the importance of OORT’s approach.
“A front-page Kaggle ranking is a strong social signal, indicating that the data set is engaging the right communities of data scientists, machine learning engineers and practitioners,” said Ramkumar Subramaniam of OpenLedger.”
Lex Sokolin from AI venture firm Generative Ventures, added that crypto projects like OORT are proving how decentralized incentives can be used to organize economically valuable AI data efforts
OORT’s success comes as the AI industry faces a growing challenge of scarcity of high-quality training data as data from epoch AI, predict human-generated text data could run out by 2028. In image datasets, new tools like Nightshade are allowing artists to “poison” their images to prevent misuse, adding to the difficulty.
