About
Earn from your daily movement.
Mobotic distributes motion sensors to holders of our token $BOT, paying you for the data that tech giants usually take for free.
Robotics developers need human motion data to build the next generation of autonomous robots. Unlike ChatGPT, which can scrape the internet for text data, there are no existing methods to capture human motion data at scale - we intend to fix this.
Wear our sensors, earn $BOT tokens on BASE, help build the future.
The more you move, the more you earn.
Mobotic Ecosystem
App
Our dedicated app for iOS and Android will allow you to track your earnings, view open data bounties and buy & sell $BOT.
Motion Sensors
Our wearable motion sensors will be distributed to $BOT holders allowing you to earn tokens as you move.
$BOT Token
Our limited supply token minted on BASE serves as our reward for data-generating users.
*Images representing app and sensors are digital mockups and may only loosely resemble the finished product.
Roadmap
Feb 2025
Full White Paper Release
March 2025
$BOT Token Launches on BASE
Summer 2025
Mobotic App and Integrated Wallet Launches on iOS and Android
Q4 2025
Motion Sensors Distributed to select $BOT holders and Move-to-Earn Goes Live
Mobotic - Litepaper (January 2025)
Mobotic aims to create the world's largest human motion datasets for training autonomous humanoid robotic systems. This initiative builds on a fundamental principle in artificial intelligence: the importance of comprehensive training data. Just as Large Language Models (LLMs) like OpenAI's ChatGPT require extensive text data for optimal performance, autonomous robotic systems need vast amounts of human motion data to achieve similarly generalisable capabilities.
The 'Scaling Hypothesis,' introduced by researcher Gwern Branwen, demonstrates that increased scale—in computing power, model parameters, and training data—correlates directly with improved AI system performance. This principle has been validated across multiple domains, from language models to self-driving vehicles and image recognition systems. However, autonomous humanoid robotics faces a unique challenge: unlike other AI applications that can leverage existing data sources, such as the internet for LLMs or Tesla's vehicle fleet for autonomous driving, there is no comparable repository of human motion and decision-making data.
While this valuable data exists in 8 billion people’s daily movements, it remains largely uncaptured and unutilised—a phenomenon we term the 'data value gap.' Mobotic proposes to bridge this gap through an Uber-style micro-economy centred around human motion data collection, powered by our $BOT token launched on BASE
Our approach involves distributing motion sensors to qualifying $BOT holders who maintain a specified token threshold (to be determined based on market conditions at hardware launch). Participants earn additional tokens by wearing these sensors during their daily activities, contributing to our growing motion database.
This 'move-to-earn' model distinguishes itself from competitors by directly connecting user activity to tangible market value. Revenue generated from licensing our datasets to developers will be systematically channeled back into the Mobotic ecosystem through value-accrual mechanisms, creating a sustainable growth cycle that increases token value and enhances data collection incentives. This value-driven ecosystem propels the advancement of humanoid robotics while delivering measurable benefits to our community of users and token holders.