The Compounding Data Engine accelerating Physical AI Robot intelligence isn't built by a few — it's built by all.
axisrobotics.ai
Joined November 2025
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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: hub.axisrobotics.ai
We're building a multi-layered robotics architecture, where the LLM drives high-level reasoning and skill harness.
Here's a demo. The task: use the right arm to arrange three objects from the tray in a row along the X axis of the table, ordered by height from tallest to shortest.
You can see the agent turn the task into continuous motion through skill harness, linking scene understanding, height-based ordering, and placement planning to physical execution.
This is an exciting start.
$AXIS staking is live on @HTX_Global with up to 150% APY ⬇️
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@axisrobotics
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Announcing the $AXIS Token Buyback
Our data engine is powering Physical AI applications across real-world scenarios. We want every contributor to share directly in it.
We're launching the $AXIS token buyback, with our first $150K tranche already complete.
1. Our commercial deals follow a pilot-first model. Framework agreements are signed only after a successful pilot, and payments are released in tranches against delivery milestones.
2. Going forward, a portion of the net profit from our commercial contracts is allocated to buy back $AXIS as cash is collected.
A public buyback report is published each quarter, with on-chain treasury records anyone can independently verify. All repurchased $AXIS is transferred to the public treasury.
Treasury address: 0xfC8c6ABC0742E64c13d6B0bAC1fCD7e604eC7Dc5
See the full details: docs.axisrobotics.ai/economi…
You can verify every step on-chain:
TWAP order: explorer.cow.fi/base/twap/17…
Treasury transfer: basescan.org/tx/0x71cfbe3d27…
A complete tutorial by our top contributor ⬇️
Some Tips and Tricks I use on @axisrobotics
i tried to simplify the process as much as possible😎
Product Update 🛠️
We've reduced the number of open task slots. Here's why.
1️⃣ GPT-6 can now solve simple tasks and generate reliable trajectories for them. We'll further reduce repetitive collection work as we move forward.
2️⃣ High-quality human demonstrations remain essential for complex tasks. These demonstrations carry far more value than routine trajectories.
Season 1 focused on diverse human input for pretraining. With that foundation in place, our focus moves to RL, experts, and distillation. A tighter slot structure supports this shift directly, and keeps resources concentrated on high-quality feedback and practical value.
See our high-level technical roadmap ⬇️
How should VLAs learn from naturally suboptimal robot demonstrations?
Introducing AXIS-Bench: What Matters in Quality-Aware VLA Pretraining, a benchmark and empirical study of how demonstration quality should be defined, labeled, and used during pretraining.
Across three VLAs and 24 downstream tasks, we systematically compare quality-aware learning choices and find that no single recipe works for every model.
A collaboration with researchers from @GeorgiaTech @CarnegieMellon @UCBerkeley @NTUsg @NUSingapore @RiceUniversity @UCRiverside @TAMU.
Details & Companion Dataset Release ⬇️
6/7 Data Release
Axis Dataset V1 launched in August. We've since built Dataset V2, now covering 1,092 tasks and 2.35M episodes (including camera augmentation). The companion datasets used in AXIS-Bench are all curated from the V2 pool:
• Pretraining dataset. 5,000 simulated Franka demos across 731 tasks, with quality labels and frame indices.
• Benchmark dataset. 354 fine-tuning demos across 24 held-out tasks, with task definitions and success checkers, scene assets, and evaluation layouts.
• Sim-to-real pretraining dataset. 19,250 replayable simulated episodes across 663 tasks, ready to re-render onto your own workspace for pretraining before real-demo fine-tuning.
The two efforts serve complementary goals: Axis grows the data resource, while AXIS-Bench studies how data quality and training choices affect downstream VLA performance.
Introducing Axis Dataset V1 - the simulation dataset for scalable robot manipulation.
Can noisy, crowdsourced simulation data support embodied pretraining? Yes—with enough coverage and diversity.
Continual pretraining on AXIS dataset V1 lifts π0.5 from 83.9% to 88.8% on LIBERO-Plus, with performance improving consistently as the pretraining data scales from 25% to 100% of the full dataset, showing no clear saturation.
Built with researchers from @GeorgiaTech @UCBerkeley @TAMU @JohnsHopkins @Penn @UMich @NUSingapore @NTUsg.
➡️Related links:
Paper: arxiv.org/abs/2607.21588
Dataset: huggingface.co/datasets/axis…
Project Page: axisaiorg.github.io/AXIS-V1/
GitHub Codebase: github.com/AxisAIOrg/Axis-V1…
7/7 Links
Explore AXIS-Bench and our broader data resources:
Project Resources:
Project page: axis-bench.github.io/
Paper: arxiv.org/abs/2610.18869
Code: github.com/axis-bench/axis-b…
Try Axis Hub: hub.axisrobotics.ai/
Datasets:
Axis Dataset V2: huggingface.co/datasets/axis…
Pretraining: huggingface.co/datasets/axis…
Benchmark: huggingface.co/datasets/axis…
Sim-to-real pretraining: huggingface.co/datasets/axis…
We hope AXIS-Bench enables more reproducible research on learning from imperfect demonstrations.
Axis Robotics retweeted
Top highlights this week:
• X Launch: @axisrobotics
• Integrated on @Pumpfun for seamless, secure access to assets on X Layer and 140+ chains
• Updated Gas Station for seamless swaps using USDT, USDC, or USDG without needing to top up your gas token balance.
Statement on the $AXIS Sell-off of 28–29 October
Over the past two days, a series of addresses sold a large volume of $AXIS on-chain. We want to set out clearly what these tokens were and what we are doing about it.
1. No team or investor tokens were sold.
All Core Team and investor allocations, together with every other locked allocation, 835,000,000 $AXIS (83.5% of total supply), remain in the vesting contract, which is jointly administered with Binance: 0xAFE41cfd4C21f1D896678e32C5AD456ea41835e6. Anyone can verify the balance on BaseScan. Not a single token has left it, and none unlocks before the 12-month cliff.
2. Where the sold tokens came from.
The tokens sold came from the initial circulating supply set out in our published tokenomics, specifically part of the Ecosystem allocation. Many ecosystem recipients are not crypto-native, so their allocation was delivered through a single OTC counterparty, under a written agreement that includes lock-up terms.
3. What we believe happened.
The pattern of the sales, which went through exchange deposit routes and hundreds of fresh addresses within hours of delivery, strongly suggests that the OTC counterparty sold these tokens on the open market. If so, this is inconsistent with the agreement.
4. What we are doing.
- We have suspended all further dealings with this counterparty.
- We are reviewing the agreement with legal counsel and will pursue every remedy available under it.
- Going forward, any remaining Ecosystem tokens will be distributed only through on-chain vesting.
The team‘s tokens remain locked, and our commitment to building Axis is unchanged.
Axis Robotics retweeted
MEXC Airdrop+ Event!
▸ $AXIS @axisrobotics
▸ Event Period: Oct 27, 2026, 13:00 (UTC) – Nov 3, 2026, 13:00 (UTC)
Details 👉
mexc.com/announcements/artic…
We're back with a second X Launch for Axis Robotics.
Trade $AXIS from now till Oct 29, 10am UTC and rank among the top 8K traders by volume to share a 2M AXIS prize pool.
Start here: web3.okx.com/ul/4ZbjPI
