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- The last but not the least of all the 4 trainers of robot trainers. Featuring @Boijerjer Bob-The-Sponge! See how he completed the 5-star Difficulty Challenger Task in @axisrobotics. LFG @axisroboticsph Philippines family! #AxisRobotics #SeeTheUnseen #Robotics #Innovation6214374
- Meet @Aishie_Talks , our host for the Axis Robotics PH Community Meetup this June 22! 🎤✨ Founder of Ikigai, Web3 advocate, and host of Onchain She Leads empowering communities through technology. Just 4 days left! 🚀 Register now: #AxisRobotics #AxisRoboticsPH
Axis Robotics Philippines @axisroboticsPhAXIS ROBOTICS PH COMMUNITY MEETUP 🇵🇭 Grabe ang suporta ng komunidad! Umabot na tayo sa 50+ registrations para sa nalalapit nating community meetup. Makisama sa kapwa builders, contributors, ambassadors, at @axisrobotics pioneers para sa isang gabi ng networking, makabuluhang usapan, eksklusibong @axisrobotics updates, community games, giveaways, at marami pang iba. 📅 Hunyo 22, 2026 🕕 6:00 PM – 9:00 PM (GMT+8)📍 LOLA Café, S'Maison, Pasay City 🎟️ Mag register : Magkita-kita tayo at sama-samang tuklasin ang kinabukasan ng Physical AI. #axisrobotics #axisroboticsph2313271.4K - AXIS ROBOTICS PH COMMUNITY MEETUP 🇵🇭 Grabe ang suporta ng komunidad! Umabot na tayo sa 50+ registrations para sa nalalapit nating community meetup. Makisama sa kapwa builders, contributors, ambassadors, at @axisrobotics pioneers para sa isang gabi ng networking, makabuluhang usapan, eksklusibong @axisrobotics updates, community games, giveaways, at marami pang iba. 📅 Hunyo 22, 2026 🕕 6:00 PM – 9:00 PM (GMT+8)📍 LOLA Café, S'Maison, Pasay City 🎟️ Mag register : Magkita-kita tayo at sama-samang tuklasin ang kinabukasan ng Physical AI. #axisrobotics #axisroboticsph
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#Axisrobotics closed September by pointing to scale rather than promises. The team said it had passed 5 million robot trajectories on Base, with the count now above 6 million, and called its Franka simulation set the most downloaded open-source Franka manipulation dataset on Hugging Face. The community sale on Sonar drew 2,472 participants and roughly $2.39 million in USDC commitments against a $1 million cap, which the company described as the most participated Sonar sale of 2026. It also noted a workshop paper accepted at IROS 2026, a meeting between its CEO and Brian Armstrong in Singapore, and a run of contributor campaigns. What @axisrobotics is actually running is a browser based system in which people teleoperate simulated robot arms and generate training data, with accepted trajectories recorded on Base. The public sale priced the token at $0.10, implying a $100 million fully diluted valuation, and offered 1% of a 1 billion supply. Vesting was later adjusted to 25% unlocked at TGE plus a commitment based bonus, with the rest subject to a six month cliff and six months of linear release. The activity and seed backing are real enough to take seriously, but the valuation, the token’s utility, and the gap between crowdsourced simulation and reliable real world robot performance remain open questions.2271175478
Axis Robotics Challenger Program 최신 소식 정리 #AxisRobotics #PhysicalAI #SeekTheUnseen 요즘 @axisrobotics 로봇 트레이너들 대상으로 제대로 한 단계 올리는 프로그램이 나왔는데, 하나씩 뜯어볼게요. 🎉 Axis Challenger Program 본격 오픈 기존 일반 태스크보다 훨씬 어려운 고난이도 태스크만 모아둔 전용 풀이 열렸어요. - 포인트가 일반 태스크 대비 2~3배 더 많이 들어옴 - 아무나 못 들어가고 화이트리스트 지갑만 접근 가능 진짜 탑 퍼포머들만 골라서 어려운 일 시키고, 보상도 제대로 주는 구조네요. “Seek the Unseen” 배지가 포인트예요. 👥 누가 들어갈 수 있나? (Eligibility) 매주 알고리즘으로 전체 기여 히스토리를 똑같이 평가해요. 두 가지를 똑같이 봐요. - Volume: 얼마나 다양한 태스크를 했는지 + Pre/Post- training 둘 다 참여했는지 + 검증 통과율이 지속적으로 높은지 - Quality: 같은 태스크를 한 다른 사람들 대비 내 퍼포먼스가 얼마나 일관되게 좋은지 한 주만 열심히 한다고 되는 게 아니라, 꾸준함이 중요해요. 배지가 Portfolio에 불이 들어와 있으면 바로 입장! 🚀 어떻게 시작하나? Axis Hub 들어가서 Portfolio 열고 “Seek the Unseen” 배지 확인 배지 켜져 있으면 Challenger Program 존으로 들어가서 튜토리얼 보고 바로 실행 아직 안 켜졌다면? 패스율 높이고 다양한 태스크 계속 하면서 기다리기 화이트리스트는 매주 월요일 12:00 SGT에 갱신되고, 태스크는 월요일 16:00 SGT에 배치로 떨어집니다. 선착순이라 배지 있으면 빨리 잡아야 해요. 💡 결론 Physical AI 데이터 엔진이 점점 더 고품질·고난이도 쪽으로 가는 신호 같아요. 쉬운 태스크만 반복하는 것보다, 퀄리티 있게 꾸준히 하는 사람들이 이제 더 큰 보상을 가져가는 구조로 바뀌는 느낌. 로봇 지능은 소수만 만드는 게 아니라 모두가 만든다는 철학이 담겨 있네요 뱃지 만들어야 겠지?
YaYa @ThirstyApeClub토크노믹스 관련해서 @axisrobotics 핵심만 쏙쏙 정리 기본 정보 - 총 공급량: 10억 개 고정 (인플레이션 없음) - TGE 시 유통량: 1.65억 개 (16.5%) - 완전 언락: TGE 후 35개월 배분 구조 구분 비중 Ecosystem 51.08% Contributor Rewards 10% Core Team 15.2% Private A + B 16.47% Liquidity 6% Sonar (커뮤니티 세일) 1% Kaito 0.25% 팀 + 프라이빗 합계 약 31.67% → TGE 때 0% 언락, 12개월 클리프 후 24개월 선형 베스팅 언락 포인트 TGE 때 바로 풀리는 주요 물량 • Ecosystem 일부 (8%) • Liquidity 전체 (6%) • Contributor Rewards 일부 (2%) • Sonar 일부 + Kaito 전체 • 팀·투자자 물량은 초반에 안 나옴 → 초반 매도 압력 상대적으로 낮음 기여자 에어드랍 (가장 관심 많은 부분) • 총 10% (1억 개) • 시즌 1 (TGE 전 시뮬레이션): 4% - TGE 때 50% 언락 - 나머지 50%는 T+3, T+6에 분할 • 시즌 2 (TGE 후 Sim-to-real): 6% → 상세 조건은 시즌 오픈 시 공개30434562- 토크노믹스 관련해서 @axisrobotics 핵심만 쏙쏙 정리 기본 정보 - 총 공급량: 10억 개 고정 (인플레이션 없음) - TGE 시 유통량: 1.65억 개 (16.5%) - 완전 언락: TGE 후 35개월 배분 구조 구분 비중 Ecosystem 51.08% Contributor Rewards 10% Core Team 15.2% Private A + B 16.47% Liquidity 6% Sonar (커뮤니티 세일) 1% Kaito 0.25% 팀 + 프라이빗 합계 약 31.67% → TGE 때 0% 언락, 12개월 클리프 후 24개월 선형 베스팅 언락 포인트 TGE 때 바로 풀리는 주요 물량 • Ecosystem 일부 (8%) • Liquidity 전체 (6%) • Contributor Rewards 일부 (2%) • Sonar 일부 + Kaito 전체 • 팀·투자자 물량은 초반에 안 나옴 → 초반 매도 압력 상대적으로 낮음 기여자 에어드랍 (가장 관심 많은 부분) • 총 10% (1억 개) • 시즌 1 (TGE 전 시뮬레이션): 4% - TGE 때 50% 언락 - 나머지 50%는 T+3, T+6에 분할 • 시즌 2 (TGE 후 Sim-to-real): 6% → 상세 조건은 시즌 오픈 시 공개
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Role Miracle Ayomide(✱,✱)@themiraculous01Most beginners struggle with Multi-Embodiment tasks.. Here's a tutorial that makes them easy. 🎯 For the #Axisrobotics Tutorial Contest, I created a detailed walkthrough covering the essential controls, movement, rotation, object interactions, to help new contributors complete⤵️Role Miracle Ayomide(✱,✱) @themiraculous01After completing 185 trajectories on @axisrobotics , I've realized something most people overlook. The biggest reward isn't the 𝗮𝗶𝗿𝗱𝗿𝗼𝗽. It's what you learn while 𝗰𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗻𝗴. 🧵 @chris_anm01 @plpiaoliang2315582.7K- Role Miracle Ayomide(✱,✱)@themiraculous01After completing 185 trajectories on @axisrobotics , I've realized something most people overlook. The biggest reward isn't the 𝗮𝗶𝗿𝗱𝗿𝗼𝗽. It's what you learn while 𝗰𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗻𝗴. 🧵 @chris_anm01 @plpiaoliang
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Nadeem king@Nadeem12x📋 Axis Robotics Daily Update :- 04/09/2026 @axisrobotics 🤖 Another day of exploring testing and learning with Axis Robotics. Today focus testing interactions, movement and system responses. Daily Routine Learn → Test → Improve → Repeat @axisroboticsin_ #AxisRobotics
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🪂 AXIS Airdrop Checker is Now LIVE! Eligible users can now check their token allocations ahead of the official claim portal opening. @axisrobotics 🔹 Allocation Checker: 🔹 Claim Portal Launch: October 21 at 12:00 UTC #AxisRobotics #AXIS #Airdrop #Web3 #Crypto #AirdropChecker
8129511- #AXISrobotics is working on a problem that doesn’t get enough attention in robotics: data. A robot can have a great model and still fail because it simply hasn’t seen enough real variation. @axisrobotics turns human interaction with simulated robots into structured training data, creating a way to scale the demonstrations needed for better manipulation policies. What makes the approach more interesting is the feedback loop. Instead of stopping at data collection, AXIS is building toward a system where model failures can be corrected by humans and fed back into training. That turns every failure into another useful datapoint. If this loop works at scale, the real product isn’t the simulator or the interface. It’s the continuously improving data engine underneath.55039145
- Nadeem king@Nadeem12xTask completed on @axisrobotics 🤖 Another successful task checked off ✅ Small task but a great step toward improving robot manipulation and real world task learning. 🤖 One step closer to smarter robots. Building. Learning. Repeating. #AxisRobotics @axisroboticsin_7214160
LuxuryNad@luxurynad@axisrobotics@axisrobotics Allocation Checker is LIVE! CONGRATS to everyone who qualified! My allocation: 👀 $AXIS Supply: 1B $AXIS Claims open today Oct 21, 12PM UTC ⁉️ What’s your price prediction? I’m estimating $0.1 - $0.2 💭 WAGMI! #AxisRobotics #Allocation #Axis #Airdrop #Claim81123.8K
Spent some time completing a few Axis robotics tasks Not every attempt was perfect, but each one helped me understand the task better and improve. Still learning, still contributing. #AxisRobotics @axisroboticsin_ @axisrobotics9018326
Why is it that sadness just strikes when I should be excited the most? Just checking how well I did with X and its engagement for @axisroboticsPh The #Philippines Regional X account has the most number of followers! #AxisRobotics Cc: @irisle_growth @plpiaoliang
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Axis Robotics ($AXIS) 🤖 The future of AI Axis Robotics ($AXIS) is helping drive the next wave of Physical AI 🚀 Physical AI is just getting started. #AxisRobotics #PhysicalAI #Robotics #AI @axisrobotics
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hannyusri@0xHannyusriI returned to my routine after 3 days because my laptop charger exploded so my laptop couldn't turn on, resulting in a lot of task @axisrobotics which was missed #AxisRobotics #AxisRoboticsCommunity
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Repetition is the ultimate shortcut to speed and higher scores in @axisrobotics Watch the video: First attempt took 7 seconds, but the second run dropped down to just 5 seconds! Practice cut the time and bumped up the average score. 📈🔥 #axisrobotics #physicalai11319527- Axis Robotics @axisroboticsAxis Weekly This week, we continued strengthening our closed-loop robotics data pipeline, from TaskGen and simulation infrastructure to failure recovery and asset-level augmentation. Key updates: - Task generation: We completed asset scan and merged it into TaskGen, helping generated tasks reason over available assets, scene layouts, long-horizon workflows, and multi-embodiment settings. - Simulation infra: We improved MuJoCo verify, replay, and scene-variant workflows, with fixes around repeated downloads, caching, compatibility, and long-horizon multi-asset task stability. - Robot controls: We cleaned up gripper behavior, IK, teleoperation, and the control panel based on feedback from longer-horizon and multi-asset tasks. Failure recovery: We continued building a pipeline to turn failed and near-failed grasping states into reusable data for recovery learning. - Asset augmentation: With academic collaborators, we advanced a shape augmentation direction that can expand one seed asset into many physically plausible object variants. A closer look at this week’s progress 🧵191229828
Axis Robotics@axisroboticsAxis Weekly This week, we continued strengthening our closed-loop robotics data pipeline, from TaskGen and simulation infrastructure to failure recovery and asset-level augmentation. Key updates: - Task generation: We completed asset scan and merged it into TaskGen, helping generated tasks reason over available assets, scene layouts, long-horizon workflows, and multi-embodiment settings. - Simulation infra: We improved MuJoCo verify, replay, and scene-variant workflows, with fixes around repeated downloads, caching, compatibility, and long-horizon multi-asset task stability. - Robot controls: We cleaned up gripper behavior, IK, teleoperation, and the control panel based on feedback from longer-horizon and multi-asset tasks. Failure recovery: We continued building a pipeline to turn failed and near-failed grasping states into reusable data for recovery learning. - Asset augmentation: With academic collaborators, we advanced a shape augmentation direction that can expand one seed asset into many physically plausible object variants. A closer look at this week’s progress 🧵1005117126.5K- 3M trajectories. 🔥🤖 Mula 1M noong June 7, ngayon 3X na ang tinaas ! 🚀 123K+ contributors worldwide. @base is powering the future of Physical AI and @axisrobotics is just getting started. #AxisRobotics #AxisRoboticsPHAxis Robotics @axisrobotics2424422.3K
- Axis Robotics@axisroboticsOur robotic data engine on @base just hit 3M trajectories. 1M on June 7. Now 3x. Generated by 123k+ contributors worldwide, with contributions recorded, verified, and rewarded on-chain. @base is the Hub for Physical AI, and we are accelerating it at a scale you've never seen.1737545444.5K
- looked into @axisrobotics today and the idea behind it is pretty interesting. we usually talk about better models, but robotics has another bottleneck: getting enough useful data. #AXISrobotics is basically trying to turn human interaction into training data for robots. the part i find interesting is the feedback loop when a model fails, that failure can become the next thing it learns from. still early, but this is probably one of the pieces Physical AI needs to scale.39031137
𝗡𝗔𝗬𝗘𝗠@Nayem885924Building the future, one task at a time 🤖 @axisrobotics is pushing robotics forward with real-world human demonstrations and diverse manipulation tasks. Humans demonstrate. Robots learn. The future gets smarter. 🦾 #AxisRobotics #Robotics #AI #Base
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