# How does the conversion work? Our Artificial Intelligence (AI) based algorithm detects if the user works out or tries hacking, and calculates the reward accordingly. The rewards for the user's physical effort are calculated as follows: **1,000 indoor or outdoor steps = up to 1 SHAPE token** **Minimum required 5 minutes of effort: up to 1,66 SHAPE tokens** **Every minute (60 seconds) of extra effort after the first 5 minutes: up to 0,33 SHAPE tokens.** Any workout session or physical activity session shorter than 5 minutes: 0 (zero) SHAPE. Less than 1,000 steps = 0 (zero) SHAPE. The number of tokens is granted only if there are "thousands" of steps and "minutes" of physical effort. There will be no token reward for "tens" or "hundreds" of steps. There will be no token reward for seconds between workout sessions. **Example:** Steps - there will be no token reward for the number of steps up to 1,000 or between 1,001 to 1,999; the same applies for steps between 2,001 and 2,999 etc. ONLY 2,000 steps or 3,000 steps are rewarded, not 2,678 steps. Workout - there will be no reward for the seconds between minute marks (for instance - no reward for 15 minutes and 47 seconds, but reward is received at 15:00 or 16:00 minutes). **Important:** Max 140,000,000 of tokens can be mined every year for the next 5 years. All 1-year tokens will be split in 365 blocks, each with 383,561 of tokens rewards. 100% of the SHAPE tokens that will be collected from users in exchange for their acquisitions of significant discounts from our program partners will also be burned in order to allow more growth for investors and an equitable community. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://inshape.gitbook.io/whitepaper/rewards-structure/how-does-the-conversion-work.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.