Joined December 2016
- Tweets 9,972
- Following 1,889
- Followers 697
- Likes 22,494
1,077 Photos and videos
Pinned Tweet
Jun 9
Samahan niyo kami sa exclusive at invite-only na gabi kasama ang @axisroboticsPh community dito mismo sa Pilipinas 🇵🇭
Hindi ito yung usual crypto meetup niyo walang mahahabang presentations, walang boring na slides totoong usapan lang, magandang vibes, at masaya na community gathering😉
Halina’t makipagkilala sa kapwa AI & robotics enthusiasts, builders, contributors, at curious minds.
Makakakuha kayo ng inside look sa mga ginagawa ng Axis, eksklusibong updates mula sa team, community games, giveaways, at maraming pagkain at inumin.
Kahit nagsisimula ka pa lang sa Physical AI o matagal ka nang nagte-train ng robots sa Axis Hub, gustong-gusto namin kayong makasama.
Pag-usapan natin ang kinabukasan ng robotics habang sama-sama nating binubuo ito
see you there, kabayan!👀
DM para sa invite link o mag-comment ka lang sa baba kung sasama ka👇
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Base showed up big at @superai_conf, Asia's largest AI conference.
As the leading blockchain for AI innovation, we spent the week showcasing what becomes possible when AI meets the onchain economy.
Featuring @InvLambda and @axisrobotics building the future of AI robotics on @base.
Special thanks to @Hassan_NY, Country Director of @CoinbaseSG, for his strong support of Base and the builders in our ecosystem.
Here's how it went 👇
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Jun 12
gm
another day to locked in on @axisrobotics
i've made 200 trajectories ytd
let's push harder today
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Jun 11
i'm the fastest to complete this 5-star task on axis hub can you beat my record?
if you haven't tried it yet register here: hub.axisrobotics.ai/login?in…
it's 100% free
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Iknows (✱,✱) retweeted
Jun 10
gm CT
let's go and contribute to @axisrobotics
Who's grinding right now?
come on join me let's grind together
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Jun 10
Why AXIS Robotics data is the Backbone of Physical AI (and why you should care)
Physical AI robots that can truly act in the messy real world is bottlenecked by one thing high-quality, diverse training data
Traditional labs collect limited, expensive, and narrow datasets while Axis is building massive amounts of real robot training data through easy browser simulations and a huge global community
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Jun 10
How Easy It Is to Contribute Data
x.com/Chunkyweb3/status/2063…
no robot no expensive setup needed
Go to hub.axisrobotics.ai/login?in…
Log in using Google / X / Wallet takes seconds
Jump into simulation tasks
Control virtual robots with mouse/keyboard it's just feels like playing a game
Complete tasks → your trajectories automatically become training data
Jun 7
Just nailed the "Put the Churro on the Plate" Multi-Embodiment task for @axisrobotics x @BitRobotNetwork Alliance
Watch me control the robots in real-time and successfully complete the challenge
If you want to contribute go here and sign-up
hub.axisrobotics.ai/login?in…
This one was super fun coordinating different embodiments to grab, move, and perfectly plate the churro felt next-level
More task incoming
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Jun 10
Why you should lock in on Axis now?
This is the early stage where contributors become part of the core network the data moat they’re building grows every single day as more labs and companies plug into this ecosystem, early participants will benefit massively through incentives, governance, and asset ownership
physical AI isn’t coming it’s being built right now by all of us
Start contributing today: hub.axisrobotics.ai/login?in…
Who’s already in?
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Jun 10
This is exactly the kind of rigorous scaling evidence the field needs. 12.9 pts over baseline (and beating volume-matched RoboCasa) clear scaling law with more AXIS data is massive!!
The 23.2 pt jump on Layout perturbations especially validates the semantic-preserving randomization approach.
Excited to see the full dataset model release this growable engine philosophy is the way forward.
Keep shipping Axis
Jun 10
In our conference submission, we evaluate AXIS as a growable data engine for robot manipulation through three questions:
1. Does AXIS pretraining improve π0.5 on downstream LIBERO-Plus robustness tasks, beyond a matched-volume baseline?
2. Does the gain scale with AXIS data volume, from 25% to 50% to 100% of data volume?
3. Which perturbation axes benefit the most, and do they match the diversity targeted by our augmentation pipeline?
Here, “AXIS” refers to our growable manipulation dataset snapshot built around a Franka Research 3 robot: 207 tabletop tasks across 7 scene categories, 50k human demonstrations, and 60k task/scene variants produced through cleaning and semantic-preserving augmentation.
Findings below 🧵
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Jun 9
Goodluck!!
Jun 9
GAxis (✱,✱)☀️
New week. New challenges. New access.
We’re giving away 10 BitRobot access codes over the next 72 hours.
Winners will get access to SN/04 and start earning rewards from both Axis and BitRobot.
To join:
1. Follow @axisrobotics & @BitRobotNetwork
2. Like repost this post
3. Comment with a screenshot or photo of where you’re training right now
Grinding tasks? Climbing the leaderboard?
Show us your journey.
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Jun 8
I just earned 11 points this week trading on @liquidtrading
small but consistent volume adds up grinding through the volatility and stacking those Liquid points every week
who else is trading on Liquid?
if you haven't tried it yet you can join me on Liquid and we'll both earn reward
let’s keep it going
Gliquid
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Jun 8
This week was about making the AXIS loop more scalable end to end: automating data-to-model workflows, testing recovery-driven training, expanding TaskGen coverage, and preparing the dataset and model stack for release.
The flywheel is spinning faster every week and this is how you scale real Physical AI
Bullish on @axisrobotics
Jun 8
Axis Weekly
This week was about making the AXIS loop more scalable end to end: automating data-to-model workflows, testing recovery-driven training, expanding TaskGen coverage, and preparing the dataset and model stack for release.
Key updates:
- Data-to-model automation: We used scripts to speed up and standardize several repetitive but critical workflows.
- Continuous-growth training: We completed multi-data-scale training and success-rate comparisons across several failure tasks.
- Failure task expansion: A new batch of failure tasks has been pushed to test, expanding the evaluation range for ablations across data scale, data quality, and randomization.
- TaskGen: Articulated-object generation is now merged into the automatic generation pipeline.
- Model and release prep: We finished the first round of fine-tuning, evaluation, and benchmarking, completed the dataset’s conference submission, and are now improving experimental results for release.
Details below 🧵
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Iknows (✱,✱) retweeted
🚨 #BreakingNews | @AxisRoboticsPH 🇵🇭 Grand Community Meet‑Up
Bringing together the Inner Circle: Ambassadors, KOLs, business leaders, & community partners for an exclusive presentation of the @AxisRobotics Business Model.
#AxisRobotics #AxisRoboticsPH
A thread🧵👇
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Jun 7
Just nailed the "Put the Churro on the Plate" Multi-Embodiment task for @axisrobotics x @BitRobotNetwork Alliance
Watch me control the robots in real-time and successfully complete the challenge
If you want to contribute go here and sign-up
hub.axisrobotics.ai/login?in…
This one was super fun coordinating different embodiments to grab, move, and perfectly plate the churro felt next-level
More task incoming
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Iknows (✱,✱) retweeted
Jun 7
1M trajectories generated on Axis.
A major milestone for our distributed Physical AI data engine.
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Iknows (✱,✱) retweeted
Isang napakalaking tagumpay para sa buong komunidad ng @axisrobotics ! 🎉
Ang pag-abot sa 1 Milyong Trajectories sa @base ay patunay ng dedikasyon, inobasyon, at sama-samang pagsisikap ng team at komunidad. Nakakatuwang maging bahagi ng paghubog ng kinabukasan ng Physical AI at robotics.
#AxisRobotics #axisroboticsph #Robotics
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Jun 5
Axis is leveling up big time
Moving from basic pick-and-place to real long-horizon bimanual cross-embodiment data
is exactly how you build actually useful robot foundation models
The staged checkers in sim sound especially smart for keeping data quality high without insane real-world reset costs
This is the kind of infrastructure play that separates the winners keep cooking team @axisrobotics
Jun 5
We recently launched a new set of robotic data collection tasks, with a focus on long-horizon tasks (LH) and cross-embodiment tasks (Multi Embodiment). These include bimanual teleoperation and task adaptation across different robot morphologies.
Why this matters:
1. Axis is moving toward more complex, real-world robotic tasks.
2. Long-horizon tasks make complex data collection more scalable in simulation.
3. Staged checkers turn long tasks into clearer training signals.
4. Cross-embodiment tasks help Axis support multiple robot forms and control modes.
5. Axis is improving both the diversity and complexity of data.
6. The goal is not just more data, but more valuable data.
Details below. 🧵
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