Sun

he Core Pillars of @PrismaXai AI To understand what makes this platform tick, it helps to look at it as a three-sided marketplace: The Coordination Layer: It acts as a bridge where robot owners (hardware) can meet task requesters. Instead of a single company owning all the robots @PrismaXai allows for a decentralized fleet. Human in the Loop (HITL): This is the secret sauce. High level AI often fails in unpredictable physical environments. PrismaX allows human operators to remotely control robots to complete complex tasks, which simultaneously "teaches" the AI how to handle those scenarios in the future. Data Tokenization: By performing tasks on the network, robots generate vast amounts of visual and tactile data. PrismaX treats this data as a valuable asset, often using decentralized ledgers to track ownership and reward the people providing the data. @PrismaXai @vivianrobotics @shayebackus

Last night at The Magic X, @castorhat gave a keynote: A Discourse in Physical AI. In brief: Teleoperation: the gold standard Egocentric: useful when collected right UMI & reverse teleop: trade quality for smoother data + lower capex Sim & world models: not data sources

PrismaX and Robotic Sensors 1. Vision Based Sensing @PrismaXai robots use advanced cameras and visual sensors to observe and understand their surroundings. This allows them to detect objects, analyze movement, and respond to real world conditions with improved awareness. 2. Motion & Joint Data Built in sensors continuously track joint angles, position, and movement. This data helps AI understand how robots move and interact physically, improving precision and coordination. 3. Real Time Feedback Sensors provide continuous, real time feedback during operations. This enables robots to instantly adjust their actions, resulting in smoother performance and reduced errors. 4. AI Learning Input All collected sensor data is used to train and improve AI models. High quality input leads to smarter, more adaptive, and reliable robotic systems over time. Final Thought PrismaX transforms real world sensor data into meaningful intelligence, helping robots learn faster, perform more accurately, and support the future of automation in Web3. @vivianrobotics @MaxC16134

We’re hosting our first @PrismaXai AMA on the Indian regional channel 🇮🇳, and this one won’t be the usual format. This session is designed to be more interactive, more practical, and actually useful. We’ll be covering a full breakdown of this week’s progress, sharing insights on content creation, and discussing upcoming events you should be paying attention to. Alongside that, we’ll spend time explaining how the PrismaX progression system really works, With simple tips you can apply immediately to grow faster and more efficiently. If you’re new or planning to start contributing to PrismaX, this is a good entry point. You’ll get clarity on how things work, what to focus on, and answers to common doubts that usually slow people down early on. We’ll also be taking live questions during the Space, so you can get clear, direct answers in real time. If you prefer, you can drop your questions in advance in the comments and we’ll make sure to address them. ⏰ Time: 9 PM IST (3:30 PM UTC) If you’re active in the ecosystem or planning to be, this is one session you shouldn’t miss. Set your reminder, join in, and come prepared with questions. Expect useful takeaways, honest answers, and a better understanding of how to move forward. Join the discord here - discord.gg/prismaxai @vivianrobotics

Quiet Build, Strong Setup: Why @PrismaXai Deserves Attention OpenGradient, as the first @a16zcrypto CSX-backed project to reach TGE, set the tone Scrolling through my timeline, I kept seeing people talk about it fair allocation, clear tokenomics, and how the FDV moved from around $170M to $350M+ within hours. But what really stood out was the vibe. Most of what I saw was positive, which isn’t that common after a TGE. It felt like people were actually satisfied. As contributors in PrismaX, many of us were watching closely. This wasn’t just another launch we were waiting to see how things play out. Posts like @0xvietnguyen’s : x.com/0xvietnguyen/s… reflected that same sentiment, and across the timeline, the reaction looked genuinely strong. That naturally shifts attention to what’s next PrismaX is one of those projects. It’s still low hype and that’s the point. Projects that build quietly often end up delivering more to their communities than the ones driven by noise The fundamentals are clear: - Backed by a16z with $11M - Product-first, built around real teleoperation - High-quality data from paid contributors, not simulations And the team plays a big role here @chynaqqq, @castorhat, @vivianrobotics, and @shayebackus bring real robotics and growth experience not just narrative. What stands out most is the data layer. PrismaX relies on real teleoperation, not simulated environments. Paid contributors create a natural filter less noise, higher-quality data, stronger output. From my side, I’ve been contributing early and consistently, and I’m currently ranked among the top 40 teleoperators. Being that close gives a clearer view of how the system is evolving and why it has potential. If OpenGradient was the signal, PrismaX looks like a quiet setup building toward something meaningful!