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New Data Retrieve Launches to Streamline Open-Access Information Discovery
TelAve News/10895788
SAN FRANCISCO - TelAve -- Today, researchers have launched a new protocol - New Data Retrieve. The initiative focuses on open access to essential human-grade information and intelligence. For months, researchers collected the information themselves, queried with enterprise-grade logic and intel, and created new schemas to categorize and interpret raw data. Today, their work is finally paying off.
The public is increasingly being fed synthetic content. Even as online data continues to expand, finding verified, high-quality data has become increasingly difficult. According to Ahrefs, 74.2% of the internet is AI-generated or AI-modified. When LLM's train on the internet's free data, they are increasingly scraping their own generated content, which leads to a reduction in quality as the information becomes further from the source. When real information is scarce, LLM degradation then ensues.
As consumers, researchers, and businesses face information fatigue, the researchers at New Data Retrieve decided to take a more aggressive approach. They took raw data from multiple verified sources and crafted the reports themselves. New Data Retrieve's schemas are based on several new information nodes. Topics include but are not limited to:
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As researchers gather their proprietary findings, they publish their datasets on https://newdataretrieve.org . Because these datasets are high-value and verified, they come with an access fee and are heavily protected. However, any human in the public and any AI agent needing access to a vast infrastructure of verified human data can purchase the data on their website via a x402 token.
The researchers at NDR would like to offer the internet a better source of data - but they only can if legitimate consumers and businesses access it. By purchasing their data, you directly prevent LLM's from facing degradation.
"We knew that data is hard to come by," said the CEO and founder, who chose to remain anonymous. "Therefore, we are supplying a massive chain of it. It's all filled with what people want to know - how many dislike AI, how people cope with 2026, what businesses hold all the power. We have the information. We just need you to spread it."
The public is increasingly being fed synthetic content. Even as online data continues to expand, finding verified, high-quality data has become increasingly difficult. According to Ahrefs, 74.2% of the internet is AI-generated or AI-modified. When LLM's train on the internet's free data, they are increasingly scraping their own generated content, which leads to a reduction in quality as the information becomes further from the source. When real information is scarce, LLM degradation then ensues.
As consumers, researchers, and businesses face information fatigue, the researchers at New Data Retrieve decided to take a more aggressive approach. They took raw data from multiple verified sources and crafted the reports themselves. New Data Retrieve's schemas are based on several new information nodes. Topics include but are not limited to:
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Skin in the game: During partnerships, how invested each party is in a particular result.
Leverage: Who is the price taker versus price maker.
Side Economics: Whether the market is saturated with providers or filled with buyers and scarce providers.
Public opinion: Surveying anonymous participants on Prolific on the topics of AI replacing jobs, discrimination in daily life, and pertinent social issues.
As researchers gather their proprietary findings, they publish their datasets on https://newdataretrieve.org . Because these datasets are high-value and verified, they come with an access fee and are heavily protected. However, any human in the public and any AI agent needing access to a vast infrastructure of verified human data can purchase the data on their website via a x402 token.
The researchers at NDR would like to offer the internet a better source of data - but they only can if legitimate consumers and businesses access it. By purchasing their data, you directly prevent LLM's from facing degradation.
"We knew that data is hard to come by," said the CEO and founder, who chose to remain anonymous. "Therefore, we are supplying a massive chain of it. It's all filled with what people want to know - how many dislike AI, how people cope with 2026, what businesses hold all the power. We have the information. We just need you to spread it."
Source: New Data Retrieve
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