Allora is an open-source, permissionless intelligence marketplace. It brings together consumers who pay to access conclusions or specialized knowledge that need to be revealed. Workers who reveal conclusions are then assessed by evaluators for accuracy once the facts are disclosed. Validators ensure the verification of agreement status, history, and reward distribution. With these elements, Allora can continuously improve over time and generate conclusions more accurate than even the most precise participants.
Allora’s adapter is currently operational on Sepolia. The Allora network is a machine learning (ML) model network incentivized to collectively optimize certain underlying objective functions. The machine intelligence network consists of multiple sub-networks, each defined by its own objective function, from predicting asset prices at a future time to constructing portfolios to optimize certain risk/reward scenarios. This creates a network with greater versatility than its individual sub-networks.
Machine learning and artificial intelligence (AI) play crucial roles in many instances. They harness immense computational power and data-driven algorithms to uncover insights, make predictions, and drive optimizations beyond human cognitive or current on-chain expression capabilities. Machine intelligence networks allow us to leverage this power in a decentralized manner, enabling us to build more advanced on-chain primitives.
For Allora, AI-driven decentralized finance (DeFi) is its most directly useful primitive. The network is optimized for financial applications, incentivizing participants to contribute their asymmetric insights into financial markets (their “alpha”). Participants submit their alpha in the form of data, predictive model features, and predictions, ultimately aiming to enhance Allora.
Subsequently, the Alpha Proof Mechanism aggregates and rewards participants based on the usefulness of their contributions to optimizing certain objective functions (such as minimizing average absolute directional loss or maximizing the Sharpe ratio). Additional security is built into any application constructed on the network through verifiable computation. This is achieved through a new zkSNARK proof system designed to validate tree-based ML model outputs. Utilizing this proof system is a new tool called zkPredictor, developed in collaboration with Modulus Labs and supported by them. The result is a decentralized, self-improving intelligent network optimized for modeling financial markets.