Spectral’s MACRO Score helped prove a critical mass of blockchain data is available for analysis. Find out how technologies like zero-knowledge machine learning (zkml), verifiable computing, and competitive machine learning are creating new use cases for on-chain data.
Zero-Knowledge Machine Learning offers incredible opportunities for addressing some of the basic problems with public blockchains. Here, Spectral examines the state of the art, and talks to Modulus Labs, Jason Morton, Dante Camuto, and Daniel Kang.
The first MACRO Score Capital Efficiency simulation, looking at Aave V2 Ethereum borrowers. High MACRO Score users had lower liquidation rates, repaid more often, and had healthier accounts.
Talking to Simon Emanuel Schmid, Edge & Node's Developer Experience manager about The Graph, a decentralized indexing protocol Spectral Finance uses to speed its access times and organize its data.
Spectral dives deep into the emerging reputation and identity landscape and finds a much more welcoming ecosystem than the old Dark Forest paradigm.
A primer on proof of income, an emerging aspect of web3. Find out what it is, read about key players, concepts, and how Spectral is beginning to approach the data science behind it.
By providing real-time threat awareness, financial reputation primitives, and creditworthiness assessment Spectral is helping build out web3's blockchain security stack.