PRISMAX: SCALING PHYSICAL AI There is no doubt that demand for robot technology is high, but most systems lack high-quality training data. This has led to poor performance and limited real-world use. @PrismaXai aims to fix the shortage of high-quality robotic training data. Currently most data is often expensive, biased, or locked in silos. Prismax aims to fix this shortcoming by combining robotics with decentralized technology. This approach will move humanoid robots from labs into homes and hospitals faster. PrismaX uses a decentralized structure to incentivize and verify visual data collection. Their stack focuses on three pillars: 1. Data protocols, 2. Uniform teleoperation standards, and 3. Advanced foundation models. This ecosystem allows human operators to train robots remotely while earning rewards for their work. PRISMAX FINANCIAL SUSTAINABILITY Led by a16z CSX, the startup raised $11 million from top investors like Stanford Blockchain and Volt Capital. Co-founders Bayley Wang and Chyna Qu bring deep expertise in AI and blockchain. This backing gives them the capital to expand their robot fleet. To turn this funding into real progress, PrismaX built a platform that targets AI enthusiasts to solve data challenges in exchange for rewards. These contributors help create diverse datasets, reduce bias, and improve robot autonomy. By involving a global community, PrismaX keeps human input at the center of scaling physical AI.