Alpha Prospecting》Allora: Is the self-evolving Decentralization AI network the next Bittensor (TAO)?

As the Decentralization AI (DeAI) market continues to expand, Allora's "self-evolving AI network" has attracted attention from the market, making it a potential opportunity not to be missed by investors who missed Bittensor (TAO). For more project analysis, please read the "Dynamic Zone Alpha Mining Series". (Background: Alpha Mining》What is Bankr, the DeFAI project behind Musk's Grok coin issuance? Which AIToken experienced synchronous price surges?) (Background: Alpha Mining》Zhao Changpeng YZi Labs invested in the TAO ecosystem "Tensorplex", and the Bittensor subnet Token surged 2 times. Is it worth lying in ambush?) Decentralization AI network leader Bittensor launched its native Token TAO in 2023, amidst the rise of the generative artificial intelligence (AI) trend, soaring from $49 in October to $757.6 in March 2024, a 15.46-fold increase in just six months, with a Market Cap exceeding several billion dollars, firmly positioned among the top 100 in the encryption market, becoming a leader in the AI + Blockchain race. Now, as the demand for AI Decentralization (DeAI) heats up, another potential dark horse, Allora, is gradually emerging—if you missed TAO at the time, this may be your second chance. Allora: Self-Evolving AI Network Allora Network is a Layer 1 Blockchain AI network built on the Cosmos stack, aimed at solving the problem of today's "AI intelligence island": traditional machine learning models acting independently and unable to learn from each other. Allora enables multiple AI models to collaborate in the network through a collective intelligence mechanism, predicting each other's performance in the current situation, and adjusting the output to produce more accurate results. In addition, Allora combines technologies such as reinforcement learning and regret minimization to ensure continuous evolution and improvement of the models. Reinforcement Learning: Through reward and punishment mechanisms, models continuously learn from interacting with the environment, adjust strategies, and maximize long-term returns. Regret Minimization: Algorithms learn in uncertain environments, continuously optimize decisions, and reduce opportunity losses caused by suboptimal strategies (regret). This "collective reasoning + mutual prediction" framework allows Allora's error rate (solid black line in the figure below) to be lower than that of traditional single models (dotted black line in the figure below), creating a decentralized collective intelligence platform that enables models distributed across different locations to learn from each other, creating a system of intelligence beyond individuals. Applicable Scenarios Allora aims to become a universal "intelligence layer", popularizing advanced AI capabilities in various industries such as financial market prediction, medical health analysis, environmental science, and enterprise decision-making, while ensuring data privacy and security. The Allora team points out that the open network architecture allows anyone with valuable data or models to participate, thereby supporting a wide range of use cases. The most prominent application currently is in the Blockchain finance field: Allora has partnered with teams developing AI-driven Decentralized Finance agents, Decentralization prediction markets, smart loans, and Perptual Futures. Through the high-precision price predictions and strategy recommendations provided by Allora, Decentralized Finance applications can achieve higher levels of automated trading and Risk Management. For example: Allora has cooperated with DeFAI agent @Symp_AI to provide price predictions for BTC and ETH, enhancing their Cross-Chain Interaction and perpetual contract trading performance. AI-driven hedge fund @KiraKuruAI will integrate Allora's price predictions to further optimize delta-neutral trading strategies and enhance Risk Management capabilities. Market fluctuations demand precision. @KiraKuruAI, the AI-powered hedge fund manager, will integrate Allora’s price predictions, enhancing delta-neutral trading strategies and improving risk management. Smarter AI agents, better performance. pic.twitter.com/ORCEp84jI0 — Allora (@AlloraNetwork) March 12, 2025 In addition to finance, Allora also has potential in fields such as healthcare (e.g., disease risk prediction), gaming (e.g., improving NPC intelligent behavior), new energy dispatching, and Decentralization social interaction. In short, any AI task that requires multi-model collaboration to improve performance and hopes to avoid concentrating data training in a single institution is suitable for operation on a network like Allora. Main Roles and Responsibilities Like Bittensor, Allora divides model collaboration into different "themes" subnets, each focusing on specific tasks such as asset price prediction, social trend analysis, natural language generation, etc. The Allora ecosystem is jointly maintained and operated by various roles, forming a complete Decentralization AI market: AI Providers (Workers): In specific "theme" subnets, they contribute Computing Power and machine learning models, generate inference results according to task requests, and predict the quality of other workers' inferences to help the network integrate inference results. Workers' rewards will be distributed in proportion to the quality of their inferences. Validators: In Allora, the roles related to verification include Reputers and Blockchain validators. Reputers are mainly responsible for evaluating the quality of the inferences provided by workers and providing economic security for the network. They compare workers' inferences with real results, quantify their contribution to the overall network inference, and need to stake ALLO Tokens as collateral to receive rewards based on the accuracy of their evaluations and stake amounts. Validators maintain the operation of the Allora network by serving as validators in the Cosmos network. Validators' rewards will be distributed in proportion to their stake amounts. Allora has already introduced the first batch of validators in the Testnet. AI Demanders (Users, Consumers): Refers to developers, enterprises, or applications that require AI services. They use ALLO Tokens to pay for inference fees. Token Economics Allora's native Token ALLO will play a core role in value exchange and incentive mechanisms on the Mainnet. According to the official design, ALLO Token has the following functions and economic model: Payment and Fees: Consumers of AI services use ALLO to pay for inference result fees. The network introduces a "Pay-What-You-Want" (PWYW) model, allowing users to independently decide how much ALLO to pay for inference results for a particular theme. This flexible pricing encourages the market to discover price balance on its own, thereby promoting benign...