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The Emergence of Data Science in Web3

The Emergence of Data Science in Web3

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.

The State of Zero-Knowledge Machine Learning (zkML)

The State of Zero-Knowledge Machine Learning (zkML)

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.

Proving Capital Efficiency (Part 1)

Proving Capital Efficiency (Part 1)

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.

How Spectral Uses The Graph

How Spectral Uses The Graph

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.

Defining the Reputation Stack

Defining the Reputation Stack

Spectral dives deep into the emerging reputation and identity landscape and finds a much more welcoming ecosystem than the old Dark Forest paradigm.

The State of On-chain Proof of Income

The State of On-chain Proof of Income

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.

Forecasting Risk with Predictive Algorithms and DeFi Data

Forecasting Risk with Predictive Algorithms and DeFi Data

By providing real-time threat awareness, financial reputation primitives, and creditworthiness assessment Spectral is helping build out web3's blockchain security stack.