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Grass: The First Ever Layer 2 Data Rollup

            Over the past few weeks, we’ve been releasing content to explain Grass’s role in the AI stack.  As you now know, the protocol performs a number of functions that help builders access web data to train their models with.  This is the crucial first stage of the AI pipeline and the launching point for all development.  

In Grass’s case, residential devices around the world host a network of nodes that scrape and process raw data from the web.  It cleans and converts that data into structured datasets for use in AI training.  And most importantly, it sources web data in a way that involves - and rewards - the participation of nearly a million people around the world.  It single handedly created the category of AI data provisioning, and it’s the reason some of the largest AI companies in the world have chosen to work with us.  It is the Data Layer of AI.

            At the same time, we’ve also spent the past few weeks reflecting on the current state of artificial intelligence.  We’ve asked ourselves about the most pressing issues it faces, and as a prominent piece of AI infrastructure ourselves, what we can do to solve them.  

Our conclusion is that the biggest problem in AI right now is a lack of data transparency.  One glance at the news will tell you why.  Ask yourself, why would an AI model equate Elon Musk with Hitler?  Or erase an entire ethnic group from world history?  Was it trained with bad data?  Or worse, with good data selectively chosen to give bad answers?

The answer is, we don’t know.  And we don’t know because there’s no way to know.  We don’t know what data these models were trained on, because no mechanism exists for proving it.  There’s no way for users to verify data provenance, because there’s no way for builders to verify it themselves.

This is the problem that Grass plans to solve, and we’re now building a layer 2 data rollup to solve it.  How, you may ask?

Allow us to explain. 

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