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A Vast New Data Set Could Supercharge the AI Hunt for Crypto Money Laundering
Blockchain analysis firm Elliptic, MIT, and IBM, have released a new AI detection model—and the 200-million-transaction dataset it's trained on—that aims to spot the “shape” of Bitcoin money laundering.
One task where AI tools have proven to be particularly superhuman is analyzing vast troves of data to find patterns that humans can't see, or automating and accelerating the discovery of those we can. Now, a new study—along with a vast, newly released trove of crypto crime training data—may be about to trigger a leap forward in automated tools' ability to suss out illicit money flows across the Bitcoin economy. That enormous data trove will no doubt inspire and enable much more AI-focused research into Bitcoin money laundering, says Stefan Savage, a computer science professor at the University of California San Diego who served as advisor to the lead author of a seminal Bitcoin-tracing paper published in 2013.
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