Today, we’re officially launching OpenRoboto — Bittensor Subnet 80.
We’re sharing the full vision: open weights, open data and open benchmarks, coordinated through Bittensor to continuously improve robotics models.
AI learned to write, draw, and code. The physical world is the one it's still struggling to crack.
@openroboto is going after it in the open as SN80. Open weights, open data, open benchmarks. Fine-tune the base robotics model, submit on-chain, and the best one becomes everyone's new starting point.
Closed labs hoard their robotics models. This one gets better in public, every single cycle.
A silver sponsor of Exploit 🤖https://t.co/CgJmJoRXKk
AI learned to write, draw, and code. The physical world is the one it's still struggling to crack.
@openroboto is going after it in the open as SN80. Open weights, open data, open benchmarks. Fine-tune the base robotics model, submit on-chain, and the best one becomes everyone's new starting point.
Closed labs hoard their robotics models. This one gets better in public, every single cycle.
A silver sponsor of Exploit 🤖https://t.co/CgJmJoRXKk
Announcing our partnership with @OpenRoboto as Axis Robotics expands its data capabilities into the @opentensor ecosystem
OpenRoboto is an open competition on Bittensor (Subnet 80) for continuously improving robotics models. Miners fine-tune an open base model starting from π0.5, every submission is scored in randomized LIBERO-Pro environments, and only a strictly better model becomes the new base.
As the core data engine behind OpenRoboto, Axis is supplying over 3 million multi-modal trajectories into OpenRoboto’s Open Data Pool to accelerate physical AI model training for miners across the Bittensor network. Furthermore, Axis will support OpenRoboto's authoritative benchmarking platform with its Data-to-Model Pipeline, enabling robust, auditable evaluation for both data and models across multiple benchmarks.
This partnership establishes a robust, end-to-end framework uniting distributed data collection with verifiable model evaluation.
Learn more about OpenRoboto: https://t.co/9viK2AXyfy
Bittensor brings 'worldwide contest-o-nomics' to robot AI development.
Which, hilariously, may mean humanoid AND other robotic efforts may soon find $TAO powering their leading edges.
Open weights were never the hard part. Open data is.
The Open Data Pool is live, with Axis Robotics @axisrobotics as launching partner.
https://t.co/4ynIBhHcbt
Decentralized robotics intelligence needs open data infrastructure to scale.
Congrats to @OpenRoboto on launching the Open Data Pool on @opentensor. As OpenRoboto enables open data access and model evaluation, @axisrobotics is powering the pipeline beneath with our compounding data engine.
More soon 🤝
Decentralized robotics intelligence needs open data infrastructure to scale.
Congrats to @OpenRoboto on launching the Open Data Pool on @opentensor. As OpenRoboto enables open data access and model evaluation, @axisrobotics is powering the pipeline beneath with our compounding data engine.
More soon 🤝
This is not just about better fine-tuning. If the pool gets big enough, we can pretrain our own base model from scratch.
That will take years, and we are not claiming it today.
Docs and quickstart →
https://t.co/4ynIBhHcbt
Axis collects this data without expensive hardware. Contributors teleoperate simulated arms straight from a browser, and capture real-world manipulation on a phone using hand pose tracking.
We use π0.5, developed by @physical_int, as the base model for the OpenRoboto competition.
It’s one of the strongest open VLA base models for robot manipulation today.
Training a robotics base model from scratch requires enormous amounts of diverse data. Rather than starting from zero, miners build on π0.5 and compete to improve it.
This gives every miner a strong shared model to start from.
See how it works: https://t.co/qQ67Rv5LQo
Over the past week, OpenRoboto shipped updates across the website, submission system, and benchmark evaluation pipeline.
Miners can now follow a submission from queue entry through live evaluation progress, final scoring, or rejection. Check out our tech update for the past week:
We also updated the model submission rules and documentation:
- Submit a complete merged checkpoint
- Bare LoRA adapters will not pass pre-check
- Use `https://t.co/4MJ9qvfzlA submit` to run upload, burn, and announce consecutively
- Check Scan Rejections to diagnose failed submissions
- The 0.01 challenger margin applies to the overall average score