My handmade cardboard robotic arm prototype for @PrismaXai ! I built this prototype using cardboard, paper, and a few simple materials to explore the basic mechanics of a robotic arm. It may look simple, but it reflects my interest in robotics, engineering, and building things from scratch. This is my first prototype, so there's still plenty of room for improvement. While creating it, I learned a lot about design, structure, and how robotic arms work. Every great project starts with a simple idea, and this is my first step. I'd really appreciate any feedback, suggestions, or ideas from the PrismaX community. Thank you for taking the time to check out my project!

Mission #16 Pick and Pack Pick up, sort, move, and pack everyday household items into a box or container. Use different objects and arrange them naturally while keeping the full interaction clearly visible. Important: The Steps, Required, and Do Not sections have been fully updated. Please read the mission guide carefully before recording and uploading. For this mission: - Head or face mounted phone only - Landscape mode required - Both hands must stay visible - First person POV only - 0.5x - 0.7x wide angle - Keep the box, objects, and hand interactions clearly visible Upload via ZenO Core: app.zen-o.xyz/ Your data helps build the future of Physical AI.

Good morning

What robot AI needs isn't faster reactions. It's the ability to know when it has failed. At ZenO, we ran about 3,000 experiments in simulation using the robot AI model pi0.5. When we moved an object while the robot was reaching for it and told it right away, it made no difference. The model kept looking at the scene and caught up on its own. When the robot dropped an object it was carrying, things were different. Once we told it exactly what happened ("You dropped it, start over"), the failure rate fell from 14.9% to 8.1%, nearly cut in half. So the real challenge is knowing precisely what went wrong. That requires data showing what kind of failure occurred, what the situation looked like right after, and how a person recovered from it. Most robot data today is just clean footage of success. ZenO is collecting diverse failure and recovery data to help build robot AI that can notice its own mistakes and fix them.

Making Crypto On/Off-Ramps More Trustless Buying crypto with fiat or cashing out still comes with a lot of trust, security, and compliance issues. Primus uses zkTLS to connect Web2 payments with on-chain transactions. The flow is pretty simple: • Bob locks USDC or ETH in an on-chain escrow • Alice pays through a service like PayPal • zkTLS verifies the payment details without exposing unnecessary data • The proof goes on-chain • Once verified, the escrow releases the crypto directly to Alice No need to blindly trust screenshots or manually verify payments. @primus_labs Just Web2 payment → verified proof → on-chain settlement. That’s an interesting use case for zkTLS.

Scam @ConcreteXYZ 🤣

GM GM Robotics data is not just about getting the task done. While validating on @PrismaXai, I’ve noticed that a successful episode is only the starting point. You have to look deeper: • Was the robot’s movement smooth? • Was the control precise? • How efficiently was the task performed? • Did the robot actually complete every required step? Even failed episodes matter. A failure can reveal exactly where the execution broke down and provide valuable data for improving future models. What makes the process even stronger is independent validation. Multiple validators review the same episode, helping create a more reliable consensus. If there’s no clear agreement, an expert reviewer steps in. The more I validate, the clearer it becomes: Good robotics data doesn’t just record the result. It captures the quality of the entire execution. 👉 Start validating: app.prismax.ai

Kicking off @kbwofficial week at @0xEastPoint in Seoul. The ZenO team will be around Seoul throughout Korea Blockchain Week, connecting with builders, investors, and ecosystem partners while sharing what we’re building for Physical AI. Great conversations today, and looking forward to more throughout the week. If you’re around KBW, feel free to reach out.

good morning winter coming...

Crypto on-ramp and off-ramp still has a major trust problem. With @primus_labs zkTLS, Web2 payment data can be verified without relying on a centralized middleman. Alice pays Bob through a platform like PayPal. zkTLS proves the sender, recipient, and payment amount. The proof goes on-chain, the escrow verifies it, and the crypto is released directly to Alice’s wallet. Fiat payment → zkTLS proof → on-chain verification → crypto. That’s a much cleaner bridge between Web2 payments and Web3.

Wassup everyone 👀

Primus is teaming up with @KaitoAI, and I think this could bring a lot more attention to what @primus_labs is actually building. A lot of people in Web3 still haven’t fully discovered Primus or understood the tech behind it. This partnership can help change that by connecting Primus with more creators, builders and the wider Web3 community. And it’s not just about visibility. Creators can earn a 0.24% $PRIM allocation, while Kaito stakers get 0.06%. That makes the creator side pretty interesting. If you’re already creating content around Primus, this could be a good time to stay active and contribute. More awareness. More builders. More people discovering the tech. Let’s see where this goes

What turns everyday human activity into something a machine can actually learn from? It’s not just the video itself. The value comes from how movement, context, timing, and interaction are captured and structured. That gap between raw activity and usable training data is where a lot of the real work happens. ZenO is focused on building that layer for Physical AI.

Crypto payments still have one major UX problem: wallet addresses. They work, but asking someone to copy, paste and verify a long wallet address every time isn’t exactly the experience that will bring Web2 users into crypto. zkTLS could change that. Imagine sending crypto to someone’s email, X account, or GitHub instead of their wallet address. The recipient simply proves they own that account using a zkTLS proof, then claims the funds directly to their own wallet. No need to expose a wallet address publicly. No need to reveal sensitive account information on-chain. It creates a much more natural bridge between Web2 identities and Web3 payments, while keeping the actual wallet ownership private. This is the kind of abstraction that could make crypto payments feel less like “using crypto” and more like simply sending money. @primus_labs has already built a sample payment app around this idea: pay.primuslabs.xyz

𝐏𝐞𝐨𝐩𝐥𝐞 𝐨𝐟𝐭𝐞𝐧 𝐚𝐬𝐤: 𝐖𝐡𝐚𝐭 𝐚𝐫𝐞 𝐫𝐨𝐛𝐨𝐭𝐬 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐠𝐨𝐨𝐝 𝐟𝐨𝐫? If you look online, most robot demos are crazy acrobatics dancing, flips, parkour, recovering from falls. It’s impressive, but let’s be honest… that’s not what most of us need. No one wants a robot in their home or workplace randomly doing backflips. The real value of robots depends a lot on where you are in the world. In places like the US or Western Europe, the focus is mostly on everyday tasks: • 𝗿𝗲𝘀𝘁𝗼𝗰𝗸𝗶𝗻𝗴 𝘀𝗵𝗲𝗹𝘃𝗲𝘀 • 𝗰𝗹𝗲𝗮𝗻𝗶𝗻𝗴 𝗼𝗳𝗳𝗶𝗰𝗲𝘀 • 𝗺𝗮𝗸𝗶𝗻𝗴 𝗳𝗮𝘀𝘁 𝗳𝗼𝗼𝗱 • 𝗹𝗮𝘀𝘁-𝗺𝗶𝗹𝗲 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆 Basically, robots helping automate small but repetitive tasks in daily life and business. But in regions like China or Southeast Asia, the thinking is different. Instead of replacing simple work, the focus is on advanced manufacturing. Industries like aerospace, semiconductors, and defense rely heavily on skilled technicians. That kind of work is hard to scale and mistakes can be expensive. Robotics there is seen as a way to support precision work and help industries compete globally without needing massive specialized workforces. So the real question isn’t “What can robots do?” It’s “Where do robots actually make sense?” Because sometimes the best robot isn’t the one doing flips… it’s the one quietly doing the work humans don’t have time for.

good morning

Good night everyone

Understanding how @primus_labs Network works Primus is building the infrastructure behind zkTLS, making it possible to verify off-chain web data in a decentralized way. The network has 3 main roles: • Attestors run zkTLS tasks inside a TEE and secure the verification process • Developers build zkTLS apps using the Primus SDK • Clients use those apps to request verification of specific web data The interesting part is the network economics. Clients pay fees for verification, while attestors stake tokens to participate and earn rewards for successfully completing tasks. There are also penalties for dishonest execution or repeated failures, helping keep the network reliable. In simple terms, Primus connects web data, zkTLS proofs, and decentralized verification into one network. Still early, but the infrastructure side of zkTLS is definitely something worth understanding.

Missions #14 and #15 are now live. Mission #14 Refrigerator Organizing Take out, sort, move, and rearrange food and containers inside your refrigerator. Mission #15 Food Preparation Wash, cut, peel, measure, and prepare ingredients before cooking. Important: The Steps, Required, and Do Not sections have all been fully updated. Please read the mission guide carefully before recording and uploading. For both missions: - Head or face mounted phone only - Landscape mode required - Both hands must stay visible - First person POV only - 0.5x - 0.7x wide angle Upload via ZenO Core: app.zen-o.xyz Your data helps build the future of Physical AI.

Privacy is becoming more important as on-chain activity gets more complex. @primus_labs Every transaction leaves a permanent trail. For users, businesses, and especially AI agents, too much transparency can reveal more than just balances and transfers. It can expose patterns, relationships, strategies, and intent. That’s why the conversation around privacy is changing. Privacy doesn’t mean hiding everything. It means having control over what is visible, what stays private, and what others can actually infer. As AI agents start managing money, executing strategies, interacting across chains, and handling real commercial activity, privacy becomes more than a feature. It becomes infrastructure. At Primus, we believe privacy should protect by default and reveal by design. The future shouldn’t force us to choose between transparency and usability. Privacy as infrastructure. Not spectacle. Not separation.