This document discusses using machine intelligence to analyze crypto-assets. It argues that traditional financial analysis methods do not work for crypto-assets due to a lack of fundamentals data and limited historical price data. It proposes that a new form of technical and quantitative analysis is needed based on blockchain data signals. Machine learning could help identify patterns in blockchain data to better understand and potentially predict the behavior of crypto-assets. The presenter is the CTO of IntoTheBlock and believes machine learning has potential to improve crypto-asset analysis by learning from real-time behavior and correlating on-chain data with price movements.