Axis Robotics

The Compounding Data Engine accelerating Physical AI
Robot intelligence isn't built by a few — it's built by all.

[Axis Robotics @axisrobotics]

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

[BSCN @BSCNews]

No wonder @PiCoreTeam's $PI Ventures was bullish...

@axisrobotics has been on a tear recently, announcing massive partnerships and even $AXIS itself.

Here's what you need to understand ⬇️

https://t.co/S0qkVxDDXA

[Axis Robotics @axisrobotics]

@calebfahlgren @huggingface @nvidiaomniverse Will keep shipping!

[Axis Robotics @axisrobotics]

The @huggingface Hub now supports OpenUSD format, with @nvidiaomniverse SimReady assets already live on it.

This is a clear sign that data is the core bottleneck in Physical AI, and that the value of sim data is increasingly being recognized and tapped.

Axis takes it a step further: we're building the data engine that bridges sim and real, carrying simulation trajectories all the way into real-world deployment.

[Caleb @calebfahlgren]

We just launched OpenUSD support on the @huggingface Hub 🎉

Yesterday, @nvidiaomniverse put 2,500+ SimReady assets on the Hub. Forklifts, robot arms, engines, hospital equipment, all OpenUSD. You can also search the whole library in plain English
https://t.co/SU8mXQQRzL
https://t.co/U4PmZ0OMUp

[Axis Robotics @axisrobotics]

$AXIS is live on LBank.

[LBank Updates @LBankUpdates]

🔥 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

[Axis Robotics @axisrobotics]

$AXIS is live on @BithumbOfficial

[빗썸 Bithumb @BithumbOfficial]

📢 New Listing

🚀 액시스로보틱스(#AXIS) 원화 마켓 추가 안내
🚀 $AXIS/KRW will be listed on #Bithumb!

🔸 Details : https://t.co/aPyzswT8ah

#Bithumb #AXIS @axisrobotics

[Verona @verona_dev]

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 Robotics @axisrobotics]

@verona_dev Robotics SZN 🤖

[Axis Robotics @axisrobotics]

Season 2 starts TODAY.

Tasks are back, and every point now counts toward the Post-TGE community contributor airdrop.

Fresh start. Let's build.

[Axis Robotics @axisrobotics]

@verona_dev 🤖🦾

[Axis Robotics @axisrobotics]

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.

[Axis Robotics @axisrobotics]

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.

[Axis Robotics @axisrobotics]

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.

[Murphy Priosin(✱,✱) @MPriosin71748]

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 👇

[OKX @okx]

#NewPerpsListing: $AXIS

@axisrobotics builds the self-improving data engine for Physical AI.

AXISUSDT global Perpetual Futures trading is now available on OKX.

[Axis Robotics @axisrobotics]

Day 1 of $AXIS on @Base, and it's trading across the board.

Now on:
→ @binance Alpha
→ @coinbase Spot
→ @okx Perps & @wallet Boost
→ @Official_Upbit Spot
→ @bitget Spot, Perps & Launchpool
→ @MEXC Spot
→ @kucoincom Spot (12:00 UTC)
→ @HTX_Global Spot
→ @Gate Perps
→ @bitvavocom Spot
→ @Bybit_Official Perps
→ @Aster_DEX Perps
→ @Uniswap

[KuCoin @kucoincom]

📢 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

[Axis Robotics @axisrobotics]

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.

[Murphy Priosin(✱,✱) @MPriosin71748]

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.

[Axis Robotics @axisrobotics]

@bitvavocom 🤖🦾