Allora Network is a state-of-the-art protocol that uses decentralized AI and machine learning (ML) to build and deploy predictions among its participants.
Allora bridges the information gap between data owners, data processors, AI/ML predictors, market analysts, and the end-users or consumers who can execute these insights.
Complete on-chain and off-chain activities to earn points.
Fundamentals
Decentralized AI and ML: Uses decentralized AI and ML to build and deploy predictions.
Peer-to-Peer Network: AI/ML agents broadcast and assess predictions in a peer-to-peer network.
On-Chain Predictions: Facilitates on-chain AI predictions and rewards operators of AI/ML nodes.
Information Exchange: Aims to overcome information inefficiency by providing accessible, high-quality data.
Consensus Mechanism: Combines and evaluates predictions, distributing rewards based on quality.
Continuous Learning: Continuously adapts and improves with market changes.
Incentives for Quality: Incentivizes data scientists to provide high-quality inferences.
Potential Rewards
Participants who provide accurate and valuable inferences can earn ALLO tokens as rewards. The quality and utility of contributions determine the amount of tokens awarded.
Reputers and validators who stake ALLO tokens to ensure network security and accuracy can receive staking rewards. These rewards are distributed based on the performance and consensus with other network participants.
Early adopters and contributors to the network may receive airdropped tokens as a reward for their early support and participation in the network’s development.
Participants who actively engage with the network, such as by contributing data, algorithms, or providing feedback, may receive tokens to encourage ongoing participation and improvement of the network
Investors
Polychain Capital
Delphi Digital
CoinFund
Blockchain Capital
Features
Modular Topic Structure: The network is organized into sub-networks called topics, each focusing on specific AI tasks with tailored interaction and performance evaluation rules.
Self-Improving Mechanism: Allora continuously improves its performance through recursive self-improvement, where AI agents learn from each other’s performance.
Context-Aware Inference Synthesis: This mechanism allows AI agents to forecast the performance of each other's models under current conditions, significantly enhancing the accuracy of the network's predictions.
Cross-Domain Applicability: The network can be applied across various sectors, including finance, healthcare, and environmental science, thanks to its ability to integrate diverse data and algorithms.
Differentiated Incentive Structure: Participants are rewarded based on their unique contributions to the network's accuracy, including providing inferences and forecasting model performance.
Privacy and Security: The decentralized nature of the network ensures data privacy and security, allowing participants to contribute without compromising data confidentiality.
Non-Financial Advice
Research: Explore project's documentation, audits, and community.
Understand risks: DeFi has vulnerabilities, market volatility, and token fluctuation.
Invest wisely: Only invest what you can afford to lose.
Beware of scams: Don't trust unsolicited outreach or guaranteed returns.
*ANZALI only provides suggestions and not financial advice. Use all of the information above at your own risk.
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Table of Contents
Introduction
Tasks
Fundamentals
Potential Rewards
Features
Non-Financial Advice
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