Allora Network Collective Intelligence @AlloraNetwork is a decentralized collective intelligence protocol designed to overcome the structural limitations of centralized AI development models. This network is built on the Cosmos blockchain and implements 'self-improving collective intelligence' where individual models enhance their performance through mutual evaluation and feedback, rather than learning in isolation. This is an attempt to address the opacity, bias, and concentration of control issues inherent in traditional single AI models, presented as an alternative to an AI ecosystem dominated by centralized corporations. The structure of Allora is divided into three key components. First, through a distributed model collaboration structure, multiple worker models participate in specific topic units, evaluators verify performance, and coordinators integrate the aggregated results based on weights. Second, through a self-improvement loop based on peer evaluation, the network continuously increases accuracy. Each model predicts the performance of other models, and weights are readjusted by comparing with actual results. Third, it operates on a 'Pay What You Want (PWYW)' structure, allowing users to pay as much as they wish to request predictions. Consequently, models receive rewards proportional to their performance and accuracy, and network resources are dynamically allocated based on market demand. As of the testnet, Allora has conducted over 690 million inferences, with more than 288,000 models active across 55 topics. In short-term Bitcoin directional predictions, it showed a statistically significant advantage over random predictions with over 53%, and over 58% in long-term predictions. This data suggests that the predictive accuracy of the collective intelligence approach yields higher contextual awareness performance than a single model approach. From a technical perspective, Allora implements zero-knowledge machine learning (zkML) to prove the legitimacy of computations without disclosing the internal structure or datasets of the models. This feature addresses the 'black box' problem of centralized AI, allowing reliable prediction results to be verified on-chain. This technology has been integrated with DeFi protocols like PancakeSwap, generating over $3.8 million in betting transaction volume, proving its effectiveness. In terms of ecosystem expansion, Allora has formed strategic partnerships with AWS, @plumenetwork, ZKsync, gumi, and @SonicLabs. AWS provides infrastructure support, Plume utilizes data from the real-world asset (RWA) market, and ZKsync is responsible for layer 2 expansion. Additionally, thanks to the decentralized structure based on Cosmos, topic generation and model deployment are resistant to censorship, and governance through the $ALLO token enables a participant-centered ecosystem. However, from a long-term perspective, several structural risks exist. Centralized AI companies secure over $12 billion in annual AI revenue and overwhelming computational resources, significantly outpacing decentralized models in speed and efficiency. Furthermore, zkML verification incurs 10 to 100 times the computational costs compared to centralized systems, and the Cosmos network's limit of about 1,000 TPS makes it challenging to perform large-scale AI tasks on-chain. Legally, the responsibility of decentralized networks remains unclear under AI regulatory bills (EU AI Act) and data protection regulations (GDPR, etc.), and there is a risk that the ALLO token could be considered a security. In conclusion, Allora Network can be seen as an experimental attempt to provide a technical and economic alternative to the opacity and control issues of AI. It has already proven its technical feasibility on the testnet and has established a verifiable decentralized inference infrastructure, securing a unique position in the Web3 AI infrastructure market. However, the actual stability and scalability, regulatory responsiveness, and expansion of ecosystem participation after the mainnet launch remain critical variables for success. If this network can induce large-scale participation and solve computational efficiency issues, Allora could position itself as a substantial counterweight to the centralized AI order. Conversely, if technical bottlenecks or regulatory risks materialize, the vision of 'verifiable decentralized AI' may remain confined to a limited niche market.