EigenAI Full Functionality Launched: Can EigenCloud Overcome the Uncertainty of Large Model Execution Results with an End-to-End Inference Solution? As large language models evolve from simple chatbots to intelligent agents capable of independent decision-making, an insurmountable technical bottleneck is hindering the large-scale deployment of AI: the highly uncertain nature of AI-generated content. Given the same input prompts, AI models cannot produce completely consistent outputs. This characteristic prevents large models from participating at scale in economically impactful decision-making processes. For a simple example, in an AI shopping scenario, the intelligent agent attempts to understand the user's intention to purchase goods. If, after purchase, the user receives a product that does not meet their expectations, they need to resolve after-sales issues with the merchant. At this point, it's crucial to first determine what kind of purchase instruction the intelligent agent issued. If the output is uncertain, the intelligent agent may offer a different choice during dispute resolution than its initial purchase intention, potentially causing financial losses for the user. To address this issue, EigenCloud recently launched the EigenAI platform. By building a complete technology stack from underlying hardware to consensus protocols, EigenCloud can provide users with verifiable and reproducible AI inference services under relatively secure and privacy-preserving conditions. This also lays the foundation for the deployment of AI intelligent agents in more serious fields. To better control model output, EigenAI proposes an end-to-end deterministic inference strategy. It rigorously controls and customizes each layer of the large language model inference stack, transforming the original probabilistic inference into a precise deterministic function. ✜ The preview section has ended; the remaining hidden core content is here 👇 research.web3caff.com/archives...…