.@axisrobotics Kaito x Axis Final Epoch Review Today is the final stretch of Epoch 1 for the Axis × Kaito Creator Program. The official campaign window runs from August 19 to September 18, 12:00 UTC. (AXIS ROBOTICS) Looking back at the campaign, the interesting part isn't simply the leaderboard. Kaito Mindshare became the attention layer for Axis. Creators were rewarded for making people understand and discuss Axis, while the referral multiplier added a second layer: referred users had to actually complete, pass verification on, and sign their Axis trajectories. The official formula is: Kaito Mindshare × Axis Referral Multiplier = Campaign Score (AXIS ROBOTICS) That makes the campaign different from a simple “post more, rank higher” competition. What happened during the campaign? → Axis continued scaling its data engine → 5.5M+ trajectories were reported by September 15 → 200K+ contributors were reported → Axis reached Top 2 DApp status on Base → Axis launched Challenger tasks for experienced contributors → Axis announced its $AXIS Community Sale → Physical AI partnerships and research continued expanding (AXIS ROBOTICS) And on the creator side, the program officially allows up to 10 submitted posts per epoch, with the best 6 used, so quality and performance matter more than simply filling the feed. (AXIS ROBOTICS) One important update: Axis's current official creator-program guide says the Kaito pool is 0.2% of total $AXIS supply, split between Top 1–100 and Top 101–500. An older August post referenced 0.25%, so I would use the newer official guide when discussing the current reward structure. (AXIS ROBOTICS) My takeaway Kaito didn't build Axis's robotics infrastructure. But it helped turn attention into measurable community activity. And Axis's bigger story is becoming clearer: Attention → Contributors → Trajectories → Data → Models → Physical AI That's why the final Kaito snapshot matters. Not because a leaderboard number alone proves the value of Axis, but because it shows how much attention the project managed to generate during this campaign. Final day. Final posts. Final snapshot. Let's see where the numbers settle. #AxisRobotics #AXIS #Kaito #PhysicalAI #Robotics #AI #Base

$AXIS COMMUNITY SALE REAL TALK The @axisrobotics Community Sale is finally here. $AXIS is being offered at $0.10 per token, implying a $100M FDV, with a $1M USDC raise. On paper, the numbers are interesting: → 5M+ robot trajectories → 200K+ contributors → Top 2 DApp on Base → $12M raised → Growing Physical AI infrastructure But let’s be realistic. A strong robotics project doesn’t automatically mean a strong token. The important things to watch are: → Actual revenue and customers → Token utility → TGE circulating supply → Investor/team unlocks → Real demand after listing → Whether the network continues growing The 10% TGE unlock + 6-month cliff + 90% linear vesting is a positive structure, but it doesn’t remove market risk. At $0.10, I think $100M FDV is worth watching, but I wouldn’t blindly buy just because the project has strong hype. Good project ≠ guaranteed good investment. Do your own research before committing capital. #AXIS #AxisRobotics #PhysicalAI #Robotics #AI #Base #Crypto

.@axisrobotics day How to open the drawer AXIS IS CHANGING HOW ROBOT TRAINING DATA IS BUILT One thing I find increasingly interesting about axisrobotics is that it isn't simply trying to collect more robot trajectories. It is building a closed-loop data engine for Physical AI. The idea is: → Humans generate robot data in simulation → Submitted trajectories are verified → Policies are trained from that data → The policy attempts tasks → Humans correct failures → Those corrections become new training data → The next policy learns from those corrections So instead of a one-way pipeline: Task → Data → Model Axis is building: Task → Data → Model → Failure → Human Correction → Better Data → Better Model Axis reported that August ended with 4.7M valid simulation trajectories from 200K+ registered users, alongside more than 160K downloads of its open-source datasets. (AXIS ROBOTICS) And the newest Challenger Program is another interesting step: higher-difficulty tasks are separated from the regular pool, with selection based on sustained activity, pass rate, and working across different task types. Challenger tasks earn 2–3× the Points of standard tasks. (AXIS ROBOTICS) This is the part I'm watching most closely. The future of Physical AI may not be just about bigger models. It may be about building a system that continuously discovers what robots don't know, collects the right data, and uses that data to improve the next version. That's the Axis thesis I find most interesting. #AxisRobotics #AXIS #PhysicalAI #Robotics #AI #RobotData

.@axisrobotics day 41 AXIS ROBOTICS IS NOW #1 IN KAITO ROBOTICS This is a strong moment for axisrobotics. The latest Kaito Robotics leaderboard shows Axis Robotics at #1 with 44.20% mindshare, ahead of Tesla Robotaxi at 23.26% and Waymo at 8.80%. That kind of mindshare shows how much attention Axis is currently attracting in the robotics and Physical AI space. But the bigger story is what is happening underneath that attention. Axis is building a compounding data engine for Physical AI connecting human contributors, simulation, robot trajectories, verification, training, and real-world deployment. Some recent milestones make the picture even more interesting: → 4.7M total trajectories reported by the end of August → 200K+ registered users → Around 13,500 hours of trajectory data → Top 3 DApp on Base → Open-source datasets with 160K+ downloads → Partnerships across the Physical AI ecosystem → Axis V2 introducing a continuous human-feedback loop for policy improvement (AXIS ROBOTICS) And now the Challenger Program is pushing the contributor side further, with harder tasks reserved for qualified contributors and 2–3× the Axis Points of standard tasks. The whitelist considers sustained activity, pass rate, and work across different task types. (AXIS ROBOTICS) What I find most interesting is the flywheel: More contributors → More diverse data → Better training → Better policies → Better robots → More demand for data Kaito measures the attention. Axis is trying to build the infrastructure underneath the attention. #1 on Kaito today is impressive. The real question is what Axis can build with that momentum. #AxisRobotics #AXIS #Kaito #PhysicalAI #Robotics #AI #RobotData

.@axisrobotics day 40( 10 day left) 10 Posts Submitted. 5 More to Go. I’ve now submitted 10 posts for the Axis × Kaito Creator Campaign, and there are still 5 posts left for me to complete. The current dashboard shows: → 10 posts submitted → 5 posts remaining → Around 10 days left in the current campaign → 79 link clicks → 10 sign-ups → 0 qualifying Trajectories so far So there’s still plenty of work to do. For me, this campaign is also a chance to talk about what @axisrobotics is actually building. Axis is focused on creating a data infrastructure layer for Physical AI. The idea is to turn human interaction with simulated robots into structured training data. Contributors can perform tasks such as: → Opening lockers → Opening trash bins → Picking and placing objects → Manipulating everyday items → Completing different robot-control tasks These interactions generate robot trajectories, which can be verified and processed for use in training and improving robotic policies. Axis is also working on the broader pipeline: Task Generation → Simulation → Data Collection → Verification → Processing → Training → Post-Training → Real-World Robotics That is what makes the project interesting to me. The goal isn't simply to collect a huge number of trajectories. It's about creating useful, diverse, high-quality data that can help robots learn more capable behaviors. And now I'm continuing my own contribution journey through the Kaito campaign. 10 posts done. 5 posts remaining. 10 days left. 79 clicks. 10 sign-ups. 0 qualifying Trajectories so far. Let's see how much I can improve those numbers before the campaign ends. Keep creating. Keep contributing. Keep learning. #AxisRobotics #AXIS #Kaito #PhysicalAI #Robotics #AI #RobotData

.@axisrobotics day 39 ( goal 10 reposts Today is my Birthday 🤩 ur gifts for me like, comments, repost thankyou. Another year, another chapter, and another opportunity to keep learning, building, and contributing. This year, I’ve been spending a lot of my time exploring axisrobotics and the bigger vision behind Physical AI. What makes Axis interesting to me is that it is not just about talking about robots. The goal is to build the data infrastructure that can help robots learn how to perform real-world tasks. Every small task we complete can create a robot trajectory. A simple action like opening a locker, opening a trash bin, picking up an object, or placing something in the correct position may look easy to us, but for a robot, these interactions involve movement, positioning, control, and precision. That is where the community becomes important. → Humans perform tasks → Robot trajectories are generated → Data goes through verification → Quality data can support robot training → Better data can help improve policies → Improved policies can eventually help robots perform tasks more effectively That whole process is what makes the Axis ecosystem interesting to follow. I’m still learning the platform, completing tasks, creating content, and trying to understand how this community-driven approach can contribute to the future of Physical AI. And today, since it’s my birthday, I have a small challenge for my community. I don’t want expensive gifts. I just want your support. If you enjoy my content, follow my Axis journey, or simply want to wish me a happy birthday, helping me reach these numbers would genuinely mean a lot to me. Even a simple comment or repost can help this post reach someone who is interested in Robotics, AI, Physical AI, and the future of robot training data. That’s my birthday gift from you. And tomorrow, we continue building, learning, and contributing. Happy Birthday to me. #AxisRobotics #AXIS #PhysicalAI #Robotics #AI #RobotData #Kaito Disclaimer: This post is for community discussion and personal participation only. Nothing here should be considered financial advice or a guarantee of any rewards, allocation, or future token value.

.@axisrobotics day 38 AXIS Challenger Program: Quality Matters, Not Just Quantity A new update from axisrobotics caught my attention. The Axis Challenger Program is focused on high-skill tasks with boosted Point rewards. But there’s another important detail about access. Axis says access is granted through a weekly whitelist, generated by an algorithm that applies the same checks across users’ on-platform history. Selection looks at two dimensions: → How much you’ve contributed → How well you’ve contributed This is important because it suggests that simply doing a large number of tasks isn't the whole picture. The quality of your contribution matters too. The Challenger Program appears to take this idea further by introducing more difficult tasks with boosted Point rewards. So the focus becomes: More contribution + Better contribution + Higher-skill tasks For contributors, this could make the strategy more meaningful. Instead of only chasing volume, it makes sense to focus on completing tasks accurately and building a strong contribution history. The key takeaway for me: Axis is looking at both quantity and quality. If you're contributing consistently, don't just ask how many tasks you've completed. Ask: How valuable and how well-executed are those contributions? The Challenger Program could be an interesting step toward rewarding contributors who can handle more difficult robotic tasks. #AxisRobotics #AXIS #PhysicalAI #Robotics #RobotData #AI

.@axisrobotics day 37 $AXIS: What Could the Token Be Worth? A question worth discussing as the Axis ecosystem continues to grow: If $AXIS eventually has a 1 billion total supply, what could one token be worth at different fully diluted valuations? The math is straightforward: Token Price = FDV ÷ Total Supply With a hypothetical 1B $AXIS supply: → $100M FDV = $0.10 → $250M FDV = $0.25 → $500M FDV = $0.50 → $1B FDV = $1.00 → $2.5B FDV = $2.50 → $5B FDV = $5.00 → $10B FDV = $10.00 The interesting part isn't the calculation. It's the valuation. Axis is building infrastructure around Physical AI, including robot task generation, simulation-based data collection, trajectory validation, data processing, and policy improvement. The ecosystem has also been growing rapidly, with millions of trajectories and a large contributor community. So the bigger question is: If Axis successfully turns its growing community and robot-data infrastructure into a meaningful business, what kind of FDV could the market eventually assign to $AXIS? The BaseScan screenshot is interesting, but it should not be taken as confirmation of official $AXIS launch details or final tokenomics. The numbers above are purely a hypothetical scenario based on a 1B supply assumption. Now I'm curious about the community's expectations. If $AXIS had a 1B total supply at launch, what price would you realistically expect? $0.50? $1? $2.50? $5? $10+? What's your $AXIS prediction? #AxisRobotics #AXIS #PhysicalAI #Robotics #AI #Crypto #Base

.@axisrobotics Axis Task Walkthrough | Locker Task Today I completed a task on @axisrobotics focused on a simple but important robot manipulation skill: Opening a locker and placing an object inside it. The task looks simple, but every movement matters. → Open the locker → Identify the target position → Pick up the object → Move it toward the locker → Place the object inside → Complete the task successfully I recorded the full task from start to finish so you can see exactly how it works. Watch the full video below to see the complete process. What I like about these tasks is that even a simple action like opening a locker and placing an object can become structured training data for Physical AI. Every successful trajectory adds another example of how a robot can interact with objects and complete real-world tasks. More tasks → More trajectories → Better training data → Better robots. Still contributing, one task at a time. #AxisRobotics #AXIS #PhysicalAI #Robotics #RobotData #AI

Clipur had 258,000 site visitors in July How many will it have in August? $100 to whoever guesses correctly 1. Repost this 2. Tag 2 friends in comments with your guess 3. Bookmark and set a reminder We usually get final site traffic data within 1-2 weeks

.@axisrobotics Axis Community Voting Guidelines Important Update Before voting in the upcoming community nomination, make sure you meet the eligibility requirements. To vote, you must: → Have at least 200 Trajectory Points → Have submitted your Trajectory submission for the current week → Have been a member of the server for 15+ days → Have 500+ messages before August 30 → Have completed 10x content before August 30 Voting rights Regular Members If you meet all requirements and don't hold a role, you can cast 1 vote for one member in Category X. Previous X, Y & Z Role Holders Previous role holders can cast: → 1 vote in Category X → 1 vote in Category Y Previous role holders can still vote even if they haven't submitted their current week's Trajectory. Important voting rules No duplicate or multiple voting. If duplicate votes are detected, all related votes will be cancelled. No cross-region voting. Members from other regions are not allowed to vote in another region. No bots or automation. Using bots, scripts, or automated voting methods can result in a permanent server ban. Anyone attempting to vote in a different region may receive a 7-day timeout. Violating the rules can also result in a 7-day timeout and a 1-week Nomination Ban. The guidelines may be updated depending on the situation, so everyone should check the latest announcement before voting. Vote fairly. Vote once. Vote in your correct region. #AxisRobotics #AXIS #PhysicalAI #Robotics #Community #Kaito

.@axisrobotics day 36 Axis Robotics is gaining serious attention in the Physical AI space. According to the Kaito Robotics leaderboard shown above, Axis Robotics is currently ranked #2 with 23.33% mindshare, behind Waymo and ahead of Tesla Robotaxi. But the ranking is only part of the story. Axis is building infrastructure focused on one of the biggest challenges in robotics: high-quality training data. The platform combines: → Browser-based robot simulation → Human-generated robot trajectories → Data verification and quality control → Simulation and real-world data → Policy training and post-training → Human feedback for correcting policy failures → Sim-to-real workflows for robotics companies Axis has also reported 3M+ trajectories generated on Base by 123K+ contributors, showing how quickly the community-driven data network is growing. The Kaito Creator Program adds another layer by connecting content, mindshare, referrals, and actual ecosystem participation. The interesting part is the flywheel: More contributors → More trajectories → Better training data → Better policies → Stronger robotics applications → More demand for data Kaito measures the attention around Axis. The Axis platform is focused on building the underlying data infrastructure for Physical AI. Being #2 on the Robotics leaderboard is a strong signal of growing interest, but the bigger question is whether Axis can turn that attention into a sustainable data advantage for the next generation of intelligent robots. Attention is valuable. Data is the foundation. Execution will decide the outcome. #AxisRobotics #AXIS #PhysicalAI #Robotics #Kaito #AI

.@axisrobotics Axis Team, We Need to Talk About the Task System axisrobotics, I want to raise a genuine concern about the current micro-task system. For beginner-level tasks, a normal completion time can easily be around 10–20 seconds, and even 10–15 seconds can be reasonable depending on the task. But we're seeing some tasks being completed in around 4 seconds. For example, a simple task like opening the micro-hand and placing an object inside it is being completed extremely fast. That raises an important question: Are all these completions actually coming from real contributors? If certain accounts are consistently completing beginner tasks in just a few seconds, their activity patterns should be easy to analyze. The team could monitor things like: -> Completion time -> Repeated movement patterns -> Number of tasks completed -> Accuracy and consistency -> Account activity -> Unusual behavior across multiple tasks This could help identify the difference between genuine contributors and potentially automated/bot activity. And honestly, this is frustrating for contributors who are spending real time trying to complete tasks properly. Another issue is the number of available slots. If the community keeps growing, but only around 30 tasks are available and each task has roughly 300 slots, the competition becomes extremely difficult. We understand that task availability can be limited. But as the community grows, the system should also evolve. More contributors should mean: More tasks → More slots → Better opportunities for genuine contributors The people who are actually spending time completing tasks should feel that their effort matters. I'm not saying every fast completion is automatically a bot. But when completion times become unrealistically fast and consistent, it deserves proper investigation. Axis has a growing community. The task system needs to grow with it. We want to contribute. We just want a fair system where real contributors aren't pushed aside by potentially automated activity or extremely limited slots. Hope the team looks into this seriously. #AxisRobotics #AXIS #PhysicalAI #Robotics #AI @imbananagreg @plpiaoliang

Hi Axis Creators, @axisrobotics has updated the Axis Referral Multiplier to better reward creators who bring new users into the campaign. Here’s the updated system: -> 5 qualifying referred Trajectories → 1.05x multiplier -> 10 qualifying referred Trajectories → 1.1x multiplier -> Continue earning more qualifying referred Trajectories to unlock higher multiplier tiers What counts as a qualifying Trajectory? A referred Trajectory only counts after the referred user completes all three steps: -> Completes the required task -> Passes Axis verification -> Signs the transaction on-chain So simply inviting someone is not enough. The referred user needs to actually complete a qualifying contribution. Important: Link your Axis account Creators should also make sure their Axis account is properly linked through the Kaito Pulse extension. This connection is important so your account activity can be properly recognized for the campaign. You can use both referral links You don't have to choose only one referral method. You can continue referring users through: -> Kaito referral link -> Axis Hub referral link Trajectories earned through both referral links will be combined when calculating your Referral Multiplier. So the strategy is pretty straightforward: Bring real users → Help them complete tasks → Get verified Trajectories → Increase your multiplier The update makes the first milestones easier to reach, especially for creators who are actively bringing contributors into the Axis ecosystem. #AxisRobotics #AXIS #Kaito #PhysicalAI #Robotics #AI