Caspius
46 posts
Caspius
@caspius_ai
Building the embodied AI intelligence economy
เข้าร่วม Şubat 2026
0 กำลังติดตาม1.5K ผู้ติดตาม
We've been receiving a lot of feedback on our app since the beta release yesterday.
Building in public - we welcome product feedback and bug reports in our Discord community here: discord.gg/caspius
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@caspius_ai I kept failing to upload cooking videos and lost all my energy. The cleaning video uploaded successfully but didn't earn any points.
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Announcing the Public Beta release of the Caspius app on iOS.
What will be available in the beta:
- Record egocentric demonstrations of everyday tasks across Cooking, Cleaning, Laundry, Logistics and Hardware
- Every demonstration feeds the training data behind Vision-Language-Action models
- Earn $CAS for what you contribute, available only for NFT holders - higher video quality and higher level NFTs earn more per video
NFTs in your inventory can be levelled up on our website.
This beta period will be used to gather feedback from our early community to further iterate on our protocol and mechanisms.
Just start contributing: apps.apple.com/app/id67611659…
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Tips on maximising video quality
x.com/caspius_ai/sta…
Caspius@caspius_ai
Caspius NFT holders have a duty to the network - to contribute to embodied AI intelligence. Phase 1 starts with egocentric data. Every recording you capture grows the dataset that trains Vision-Language-Action models (VLAs). For the dataset to be valuable, the network cannot accept slop - it needs high quality physical demonstrations that a robot can learn from. To enable this, we have carefully constructed the infrastructure to facilitate contributions from Caspius holders: → All demonstrations must be captured directly through the Caspius mobile app → iOS is coming soon, with Android to follow after → Other modalities (e.g. Ray-Ban Meta, Apple Vision Pro) are currently not supported but are on the roadmap What determines whether your data is usable: → A head mount is required. Hands-free recording is non-negotiable - phone head mounts are widely available on Amazon/Taobao/Temu and similar retailers. → Good, even lighting throughout the scene → Stable framing - smooth movements, no quick head jerks The single most important rule: Your hands must always be in the centre of the frame. If your hands leave the frame, the recording loses value. Quality demonstrations earn more points and make your stake in the network more valuable.
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iOS app release is almost here, and with it, the chance to contribute. Five task categories will be open to you:
Cooking - chop vegetables, stir a pot, plate a dish, season meat, knead dough
Cleaning - wash dishes, wipe counters, mop floors, scrub the sink, tidy a room
Laundry - fold a shirt, iron pants, hand wash, hang dry
Logistics - sort items, arrange shelves, stack boxes, lift and carry
Hardware - tighten a bolt, rewire a plug, drill a hole, assemble a frame
Pick a category, then record activities that genuinely fit it. Relevant demonstrations make every recording count and maximise your energy.
Have you all gotten your head mounts?
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Simulators are the prerequisite for Physical AI that understands how the world works. Real world demonstrations are key to getting us there.
Fei-Fei Li@drfeifei
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Built a leaderboard for the $VIRTUAL ecosystem.
It tracks who's actually spreading the @virtuals_io signal on X ranks accounts by real engagement (views, likes, quotes) over the last 6 months.
See the full rankings → proofofvirtual.xyz
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Caspius รีทวีตแล้ว
99% 的人把 Shift 看成了“免费清洁服务”。
他们刷到纽约预约上门、操作员戴头戴设备、你一分钱不付，就兴奋地喊：
“AI 终于走进我家了。”
但这恰恰是最大误判。
Shift 的核心，不在清洁服务本身，而在用清洁作为入口，大规模采集真实世界里人类做日常任务的第一人称动作数据。
录制完成后，所有个人痕迹都会被处理掉：
人脸模糊
音频删除
元数据清除
最后留下的，是“手怎么抓抹布、身体怎么弯腰、物体怎么被整理”这些细微动作交互。
这些数据，才是它真正有价值的商品。
用数据价值反向补贴服务，是 embodied AI 具身智能浪潮的冰山一角。
过去两年，我们听过太多“机器人要进家门”的 PPT。
模型越堆越强，仿真环境越做越真，可机器人一到真实家庭环境里，还是很容易抓瞎。
原因很简单：
它缺的从来不是算力，而是人在混乱真实环境里做事的底层动作样本。
客厅不是实验室，厨房不是模拟器。
你叠衣服的节奏、擦桌子的力度、处理突发状况时的判断，全是高维、噪声巨大、很难被模拟数据完全替代的真实数据。
Shift 把这个问题直接搬到纽约公寓里，用免费服务换数据，证明了“数据价值补贴服务”这条路能走通。
但它也暴露了天花板：
只能在纽约做
依赖中心化审核的操作员
数据最终还是掌握在 Shift 手里
真正的瓶颈，从来不是“有没有人愿意贡献数据”。
更关键的是，普通人敢不敢、愿不愿把隐私交给一个中心化平台。
这正是 $CAS（@caspius_ai）正在悄然解决的底层问题。
$CAS 做的是 embodied AI 的真实世界动作数据层。
它把采集范围严格收窄到“手部动作 + 物体交互”，比如叠衣服、整理物品这类日常任务。
视频会自动模糊人脸、去掉音频、清除所有元数据。
用户自己决定录什么，也可以匿名贡献。
它不关心你是谁。
它只学习“你是怎么做事的”。
目前 Caspius iOS App 已经上线，1000+ 小时演示数据、500+ 贡献者、20 个任务正在真实积累。
这和 Shift 的匿名化逻辑高度一致，但 CAS 把这个逻辑放到了链上：
用户可控
去中心化
可组合
带经济激励
Shift 在线下用免费清洁验证了需求。
CAS 则在链上把同一套“动作数据”变成了可全球复制、可交易、可长期持有的基础设施。
当机器人真正需要从 demo 走向每个人的家里，最稀缺的燃料会是隐私友好、高质量、持续产生的真实动作数据。
Shift 证明了用户愿意用数据换服务。
CAS 正在把这个交换关系，从纽约公寓扩展到全球每一个愿意打开手机录两分钟日常的人手里。
这才是真正的“AI 向你靠近”。
你每天无意间做的动作，未来可能会被转化成机器人可以复制的技能。
而你作为数据贡献者，也有机会参与到这波具身智能的数据红利里。
最近市场波动很大， $CAS 反而相对稳。
我觉得原因也很直接：
它踩的不是短期情绪，而是 Physical AI 最底层的燃料瓶颈。
风还没吹到所有人，但数据已经在积累，产品已经在跑，少数人已经看懂。
真正的 Shift，从来不只是免费清洁。
它更像是日常动作的数据化、金融化与机器人化。
$CAS 只是把这扇门，提前打开了一条缝。
shift@joinshiftX
Today, we're launching shift. We're starting by cleaning your apartment in New York City, for free. Here's how it works. Book a shift cleaning. A vetted shift operator comes to your home wearing one of our devices. They clean. They leave. You pay nothing. In exchange, we record the cleaning. Robotics is being built on data about how people do daily tasks, and the value of that recording is what funds the service. Anything personal in it is anonymized before the recording is processed. By now, you have heard about the shift to AI more times than you can count. About the shift toward you, the part where you actually feel it, you have heard almost nothing. Shift is what starts to make it concrete, in specific cities, with specific services. Today, cleaning in New York. Soon, handymen, repairs, and errands across the globe. And this is just one side of shift, with more on the way. Comment “shift” and we’ll send you an early access link.
中文
Caspius equipment is all set up now, just waiting for the app announcement.
@caspius_ai is going to be huge. <3 @virtuals_io
Caspius@caspius_ai
Why not upload your data onto Caspius and earn $CAS while your home gets cleaned? Sounds like a no brainer to me
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Caspius รีทวีตแล้ว
Data Network for Robots: Caspius
I’ve been following @caspius_ai for a while now, and I think a lot of people are framing it the wrong way. To be fair, I looked at it the same way for a long time. Most people see Caspius as a robotics project. Recently, I’ve started seeing it as a data network instead.
The reason AI models became so good wasn’t just because of algorithms. There was also the internet. Billions of people generated data for years, wrote text, took photos, and shared videos. Models were trained on top of all of that, on a pile of trillions of words.
In robotics, however, no such internet was ever created. You could almost say there is no archive of experiences for robots to learn from. The gap becomes obvious when you look at the numbers: even the most ambitious data collection efforts can only generate tens of thousands of hours of data per year. Compared to the amount of data consumed by a language model, that’s just a drop in the ocean. In my view, this is exactly the gap Caspius is trying to solve.
And it’s not just about quantity. Nearly all existing robotics data is collected in laboratories, controlled environments, and pre-selected scenarios designed by researchers. In other words, robots never get to see the natural messiness of real life. Yet understanding the world requires more than just seeing images. A robot needs to learn how we grasp objects, how we move, how we use a knife, and how we complete tasks in the kitchen. At its core, this means large-scale real human behavior data.
This is where Caspius does something simple but clever. You put on a rig, go about your daily life, and everything you see is recorded from a first-person perspective. That data is sold to robotics companies, and in return you earn points. Those points are converted into $CAS token rewards, while NFT holders receive increased daily data capacity. The logic is actually very simple: if you are producing the data that powers the robotics economy, you should also share in the value created by that economy.
I also like that they take privacy seriously. Faces are blurred, audio is removed, and location and device information are stripped away. The model doesn’t need to know who you are it only needs the behavior itself.
I think this is the key point most people miss. Robots do not need perfect data; they need diverse data. Different homes, different people, different habits, different objects. The messy but authentic behavioral data generated by millions of people may ultimately be more valuable than the pristine data collected by a laboratory over many years.
As for where this goes, I believe data will become extremely important for robots in the long run. Hundreds and thousands of new robots will need data, and Caspius could be far ahead of everyone else in this area. That’s why I’m quite optimistic about Caspius. Maybe it’s still very early, and maybe most people don’t see its importance yet. But if data truly is the biggest bottleneck in Physical AI, then projects solving this problem could become far more important over time. Looking at the space today, I think it’s one of the projects with the strongest vision across both robotics and crypto.
That’s why Caspius is on my radar. Because the most valuable projects are often built long before anyone realizes their significance.
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Why not upload your data onto Caspius and earn $CAS while your home gets cleaned?
Sounds like a no brainer to me
shift@joinshiftX
Today, we're launching shift. We're starting by cleaning your apartment in New York City, for free. Here's how it works. Book a shift cleaning. A vetted shift operator comes to your home wearing one of our devices. They clean. They leave. You pay nothing. In exchange, we record the cleaning. Robotics is being built on data about how people do daily tasks, and the value of that recording is what funds the service. Anything personal in it is anonymized before the recording is processed. By now, you have heard about the shift to AI more times than you can count. About the shift toward you, the part where you actually feel it, you have heard almost nothing. Shift is what starts to make it concrete, in specific cities, with specific services. Today, cleaning in New York. Soon, handymen, repairs, and errands across the globe. And this is just one side of shift, with more on the way. Comment “shift” and we’ll send you an early access link.
English
Privacy is essential in this day and age, and at Caspius we have designed our approach with this in mind from first principles. Here's how it works.
Models are trained on hand-object interaction, basically hands doing everyday tasks like folding clothes or wiping a counter. The useful part is the movement, not the person doing it.
What happens to every video captured on the Caspius app:
- Faces blurred
- Audio removed
- Metadata like username, GPS and device IDs stripped
The data stored is in line with standards set by robotics labs - privacy is key for them too and we make access to compliant data frictionless.
Ultimately, you are the first layer in the filter - you decide what you record and submit. Caspius enables you to contribute to the future of robotics without us ever knowing who you are.
English
Caspius รีทวีตแล้ว
很认可 @thedefiedge 对 Base 上 robotics × crypto 的梳理。
我自己目前最看好的，还是 $CAS (@caspius_ai )。
原因很简单：
现在大家都在聊 AI agent、机器人、physical AI，但真正卡住行业的，其实不是模型，而是「embodied AI data」。
机器人不是会聊天就够了，它得知道：
怎么抓东西、
怎么移动、
怎么在真实环境里完成任务。
而这些东西，本质上都需要海量第一视角的人类行为数据。
我觉得 $CAS 很特别是因为：它把“普通人的日常动作”变成结构化训练数据。
做饭、洗衣、整理房间这些过去毫无价值的行为，现在都能被记录、标注、训练、货币化。
Genesis NFT 的设计我也觉得很聪明：
• NFT = 数据运营商席位
• 不同身体部位 + Traits 决定专精方向
• 稀有度 / Level / Trait match 会影响 multiplier
• Fabrication 可以持续合成、繁殖、进化“血统”
本质上，它是在把数据网络游戏化。
你不只是持有 NFT，
而是在参与训练未来机器人的“动作数据库”。
最关键的一点是：
很多 robotics 项目做的是 execution layer、coordination layer、payment rails。
但 $CAS 抓的是更底层的东西：数据。
而数据一旦形成飞轮，护城河通常会比协议本身更深。
但至少目前看，它是整个 robotics × crypto 里，少数让我觉得“方向对了”的项目之一。
Edgy - The DeFi Edge 🗡️@thedefiedge
The robotics x crypto narrative is quietly getting built on Base. Not the robots themselves. The rails around them: data, ownership, payments, identity, teleoperation, and deployment. If robotics scales, that's where the value accrues. Here are some projects on my watchlist: • @virtuals_io ($VIRTUAL): Virtuals is becoming the main launchpad for robotics on Base. The key piece is Eastworld Labs, a robotics track focused on humanoid fleets, teleoperation data, and physical-world task experiments. Their ecosystem already has 30+ Unitree robots and a robotics market cap around $45M. • @caspius_ai ($CAS): Caspius is focused on embodied AI data. Robots need real-world movement, perception, and environment data before they become useful. Their recent Genesis NFT drop is tied to this data network, with contributors helping build structured training data for physical AI. • @StrikeRobot_ai ($SR): Strike is direct humanoid robotics exposure. The project focuses on industrial/security environments and has published paper, teleoperation revenue, Eastworld Labs backing, and incoming x402 integration for enterprise simulation access. • @FabricFND ($ROBO): Fabric is building rails for the robot economy: identity, wallets, payments, and task coordination for autonomous machines. If robots eventually earn and transact, this is the backend layer they're trying to build. • @shadowcleague ($SCL): Shadow is the entertainment angle: humanoid robot combat with livestreams, prediction markets, and fan-driven participation. Their first combat stream is scheduled around May 23. • @AukiLabs ($AUKI): Auki is the spatial intelligence layer. Its Posemesh helps machines understand physical space, which matters for retail, agriculture, AR, navigation, and robotics. Unreleased Token Projects: • @xmaquina ($DEUS) is the ownership angle. It is building a DAO around robotics exposure, with treasury links to companies like Figure AI, Apptronik, 1X, Agility, and Neura. The $DEUS TGE is expected on May 27. • @OrionX_Robotics ($ORION) is expected to launch on Virtuals, focused on autonomous humanoids for industrial and defense-style environments. Base is quietly becoming the center of robotics x crypto. The sector is still early, but the reason robotics is worth tracking is that projects here are trying to solve actual robotics problems. I'm pretty sure I'm missing a few projects so please lemme know!
中文
Caspius will be the gold mine for all robotics data (egocentric, teleoperation and more).
Robots need diverse data to better understand the world. What could possibly be more diverse than a decentralized network of millions of contributors?
We will scale to frontiers previously unknown to mankind.
CyberRobo@CyberRobooo
No wonder they say teleoperation is dead Peking University’s DAGroup released HumanNet, a massive 1 million hour dataset of human-centric videos that turns everyday internet footage into gold for embodied AI. It’s got first-person and third-person views, super detailed actions, object interactions, tool use, and long sequences of real behavior. Everything’s cleaned up and annotated with 3D poses, SLAM tracks, and robot-ready labels. The crazy part is,Training on just 1,000 hours of their first-person videos performs as well as (or even slightly better than) 100 hours of actual robot teleop data on downstream tasks. Basically, human videos can now stand in for expensive robot data. Scaling laws for robotics just got a whole lot more realistic. Human priors + smart curation = the future of world models.
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