About Moom

This is not a "holding tokens for interest" model, but a "consume/transaction as mining" model. You contribute to the system by trading (creating tax), and the system rewards you with USDT every hour based on the size of your contribution (the amount of destruction caused). Your goal is not to accumulate MOOM, but to become the biggest contributor to system destruction through trading, achieving perpetual dividends.

HypoMind – Hypothesis-Driven Robotic Intelligence. HypoMind is a self-developed "scientist-style artificial intelligence" framework. Its goal is to shift AI from passive imitation to active exploration, enabling it to propose hypotheses, design experiments, and verify the causal structure of the world, much like human scientists. Unlike traditional models that only execute tasks or generate scenarios, HypoMind aims to give intelligent agents the ability to think and verify autonomously. The core of the system consists of four layers: a language-based large-scale hypothetical engine, a physical simulation and reality interaction layer, a verification layer that autonomously executes verification experiments, a trust update system that accumulates knowledge through beliefs, and a strong-policy learner world model that continuously optimizes the agent's decision-making and prediction capabilities. Through this complete cycle, a verifiable and knowable world is built, allowing AI to evolve from a "task executor" to a "cognitive scientist." More importantly, HypoMind combines this cognitive process with blockchain and Real-World Assets (RWA) mechanisms to form a decentralized scientific intelligent ecosystem. In this system, the formulation, verification, and updating of hypotheses are no longer merely data processes, but rather tradable and verifiable knowledge assets. Every verified physical law, every piece of experimental data, and every optimized strategy is recorded on-chain as a real-world knowledge asset (RWA). The core token, MOOMToken, serves as the system's energy and incentive unit, used for hypothesis staking, verification rewards, and knowledge model profit sharing. Research nodes earn revenue by proposing and verifying hypotheses, while investors share in the knowledge appreciation by staking to support scientific experiments. Artificial intelligence is no longer just a consumer of computing power, but a producer of knowledge assets; scientific exploration is no longer just an academic activity, but a value-generating process that can be quantified, verified, and invested in. This concept aligns perfectly with NVIDIA's ongoing "world model" strategic direction. As NVIDIA CEO...