Axis is officially LIVE on @base. 🔵
Axis is scaling Physical AI for the real world, contributed by everyone.
You can control robots in a virtual world, generate training data at scale, and help build the brain behind tomorrow's robots. All from browser. No hardware needed.
Start building robotics intelligence today: https://t.co/xeQnZzV2WM
🔥 World Premiere #listing
🌠 $AXIS (Axis Robotics) will be listed on LBank!
Axis Robotics develops data infrastructure for robotics and physical AI.
❤️ Details: https://t.co/UWQ2PP9CQG
Robots have less than 1% of the experience language models learned from. Here’s how Axis Robotics is closing the gap, and what it’s building on Verona to make the data provable. https://t.co/FFw5pu66Lp
Axis is scaling into a model company.
We built the data infrastructure for one reason: to produce general robotic intelligence.
Our approach is centered on skill: we turn reinforcement learning experts into reusable, conditioned skills, and those skills feed a general model.
Data is the input. The model is the product, and it keeps improving on its own outputs. As it grows, the ceiling keeps rising toward general robotic intelligence.
We're just getting started.
What happens when an agent plans and reinforcement learning executes?
An agent generates trajectories for carrying a kettle and pouring water, while conditioned RL handles the low-level control with precision and robustness to disturbances.
This is the frontier where high-level planning meets reliable physical execution.
We tested @dreamlabs_ai's API on our own YAM Box from @i2rt_robotics with a natural language instruction ⬇️
We're working toward a similar vision, models that generalize across tasks and embodiments, and this is a promising glimpse of what's possible.
Tried @dreamlabs_ai’s API on our own YAM Box from @i2rt_robotics
“Pick up the blue cylinder and place it next to the red bottle.”
Still a long way from reliable deployment, but this makes us excited about the potential for zero-shot generalization across robot platforms.
Here’s how it went 👇
#NewPerpsListing: $AXIS
@axisrobotics builds the self-improving data engine for Physical AI.
AXISUSDT global Perpetual Futures trading is now available on OKX.
📢 New Listing: @axisrobotics (AXIS) Listed on #KuCoin!
Axis Robotics is building the Compounding Data Engine for Physical AI, solving robotics’ biggest bottleneck: scalable, high-quality training data.
📅 Trading Starts: 12:00 on October 22, 2026 (UTC)
💰 Deposits: Open Now (Network: BASE)
🔁 Trading Pair: AXIS/USDT
Details: https://t.co/wmwx3jMzE7
#KuListing #AXIS
Congrats on the launch! The vision of one model spanning any robot, and the API as a cross-embodiment layer, is really compelling.
We are building a self-evolving data engine for physical AI, and we've gone deep on cross-embodiment simulation. We now maintain what we believe is the largest open-source Franka simulation dataset for manipulation, and the accompanying paper was accepted to the IROS 2026 PWMS workshop: https://t.co/GlrrA1yXaI
We can train expert models with very little time and compute, in under 20 minutes on a single RTX 4090. We then pair that conditioned RL with high-level agentic planning. A couple of quick demos:
https://t.co/eVZ564a8Pl
https://t.co/VBt2LafkQa
Where we think we can add real value for Dream Labs is a benchmarking platform spanning diverse tasks and embodiments. One study built on a subset of our data pool: https://t.co/v9lqLweLXR
We'd love to explore deeper collaboration around this.
An agent generates trajectories for carrying a kettle and pouring water. Dyna2-style RL handles low-level control with precision and robustness to disturbances—beyond motion planning alone, as Qia Yuan noted.
Agentic planning + conditioned RL is a huge frontier.
The @AxisRobotics Launchpool is now LIVE!
Lock $BGB or $AXIS and share 1,333,333 AXIS.
📅 Locking period: Oct 21 - 28, 13: 00 (UTC)
Join now: https://t.co/cL1BlisGmE
Axis Robotics $AXIS is joining #Bitget Launchpool!
Locking period: Oct 21, 13:00 - Oct 28, 13: 00 (UTC)
@axisrobotics is building the compounding data engine accelerating Physical AI, enabling scalable, high-quality training data for general-purpose robotics.
Details: https://t.co/rw9k0zhxiv