
CEO @robotensor_ai, building the intelligence layer for robots. One demo in, new skill out.
Raleigh NC
Joined January 2025
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Corey Nida retweeted
🚨 Going LIVE Today at 12 PM ET!
We're diving into Bittensor SN58 Attune with the team ( @robotensor_ai )!
Join us as we break down what they're building and what's next for SN58.
🔴 Watch Live 👇
youtube.com/live/3i9F3_Ku8Fo bittensor:native
On the floor at #AllThingsOpen 2026 in Raleigh 🤖
The future of robot intelligence should be open. That's why we built Attune — @robotensor_ai s open robot-intelligence competition on Bittensor (SN58).
Building in robotics or decentralized AI? Let's talk.
attune.robotensor.ai
Corey Nida retweeted
Introducing Attune — Bittensor Subnet 58 (SN58)
The open frontier for adaptive robot intelligence.
We're excited to announce the launch of Attune (SN58), a new @bittensor subnet built by Robotensor to accelerate the development of adaptive robot models.
Today's robots are powerful, but adapting them to new tasks still requires collecting data, retraining models, and reprogramming workflows.
We believe robots should learn new work simply by being shown what to do.
Attune brings researchers, engineers, and miners together to compete in building the next generation of robot intelligence.
Our research focuses on:
- In-Context Learning (ICL) — Learning new tasks from demonstrations without retraining.
- Generalization — Adapting to new objects, environments, and robot configurations.
- World Action Models (WAMs) — Learning physical dynamics and predicting future actions.
- Efficient Inference — Moving toward real-time, closed-loop robotic control.
Our first competition, Vector, is now open. 🚀
Miners train and submit model weights, while validators evaluate performance through randomized simulation and transparent, reproducible head-to-head competitions.
Our upcoming competition, Horizon, will expand toward human-video learning, World Action Models, and efficient inference.
We believe the future of robotics will be built through open research, measurable progress, and global collaboration.
A robot should not need a new brain every time the work changes.
Join us in building that future.
🌐 Website: attune.robotensor.ai/
📖 Documentation: attune.robotensor.ai/docs
📄 Whitepaper: attune.robotensor.ai/whitepa…
💻 GitHub: github.com/robotensor/attune…
Attune | SN58 | Powered by @bittensor
#Bittensor #Robotensor #Attune #Robotics #PhysicalAI
we just launched Attune on @bittensor , subnet 58
robots are still really bad at something humans do without thinking. you show a person how to do a task once and they can do it in a different room. robots fall apart the second anything changes
so we built an open competition around fixing that
it's king of the hill
everyone trains the same 781M param network so it comes down to who trains it best. scenes get dealt after you submit, and you have to beat the current champ by 3+ points to take the crown
rewards go to the last 4 champions, not just whoever's on top right now
Horizon is next. that one is robots learning from human video, which is where this gets really interesting
if you train robot policies or have GPUs sitting around, come try to take the crown
attune.robotensor.ai
github.com/robotensor/attune…
Horizon is next. that one is robots learning from human video, which is where this gets really interesting
if you train robot policies or have GPUs sitting around, come try to take the crown
attune.robotensor.ai
github.com/robotensor/attune…
it's king of the hill
everyone trains the same 781M param network so it comes down to who trains it best. scenes get dealt after you submit, and you have to beat the current champ by 3+ points to take the crown
rewards go to the last 4 champions, not just whoever's on top right now
first benchmark is called Vector
your model gets one demo of a task, then has to do it in a scene it's never seen. 16 tasks on two Franka arms. stuff like putting a burger and fries on a tray, hammering a block, seating a phone in its stand
you can't memorize your way through it
$1B+ valuation, pitch includes robots that adapt to production changes without code updates.
The market is telling us what it wants: automation that doesn't start over every time the work changes.
Building exactly that at @robotensor_ai.
"Claude, I need a React dev to add Stripe billing to my SaaS. $1,800. Two weeks."
Claude pulled up 3 matched profiles. I asked it to compare them. It did.
I picked one. Sent a message. First commit landed 18 hours later.
No job post. No interviews. No context-setting call.
1/ Scope the work inside the conversation
Instead of opening Upwork and writing a new brief from scratch, describe the problem directly to Claude.
It turns your conversation into a structured scope — budget, timeline, deliverable, stack.
No context loss. No translation layer.
3/ Start work with full context already loaded
The freelancer gets your Claude conversation as their brief.
No 45-min kickoff call. No "can you clarify what you meant by X."
They already know the problem. They build the solution.
Try it: revolutionai.io/plan-project
2/ Review matched talent without switching tools
Proposals come back into the same session.
You can ask Claude to compare them, flag tradeoffs, or summarize what each person is actually offering.
The signal-to-noise ratio is different when you're not drowning in a platform UI.
3 ways SaaS founders hire without leaving Claude:
(The shift from tab-switching to MCP-native workflows is real — here's what it looks like in practice)
Freelance hiring in 2024: post job → wait 3 days → filter 40 applicants → interview 5 → pick 1 → re-explain context → start work
Freelance hiring in 2026: describe what you need in Claude → review 3 matched proposals → hire → work starts with full context already loaded
The hardest part of hiring a freelancer isn't finding them.
It's writing a brief that captures what you need.
Most founders spend 2 hours on that doc and still get back work that misses the point.
When the brief lives inside Claude, that step disappears.
Most freelance platforms charge 20% on both sides.
You pay a premium. The freelancer earns less. Platform wins regardless.
We charge 0% until you close a deal. Then a flat fee.
No race to the bottom. No hidden markup.
The marketplace should win when you do.


