I am making a $40 trillion bet. And I am all in.
Jensen Huang said the physical AI industry will be worth $40 trillion in the coming years. You've already seen it. The Doordash robot rolling down your street. The warehouse arm that packed your last Amazon order. This is happening. Fast.
But the teams who figure out how to train, iterate, and deploy robots quickly and cheaply? They win. Right now, most can't train, iterate on, and deploy robots QUICKLY and COST-EFFECTIVELY enough — and fall behind because of it.
And that's why we launched Cadenza CLI - the RL environment builder for physical AI infrastructure.
Our environments use abstraction to decrease redundant details in data, speeding up fine-tuning/RL processes on your physical AI projects.
→ +80% more accurate than current RL pipelines (in the same time)
→ +70% more GPU headroom per training run (reducing unnecessary compute costs)
→ Already used by robotics developers from ex-OpenAI and NVIDIA teams
Faster training. Cheaper iteration. Robots that actually ship.
If you're building in physical AI and want to move faster —> DM me. I want to hear what you're working on.
@abdalrahemank thats really interesting, I would love to expand and get uni students on this infrastructure that could give that what they need to build more efficiently.
Do you have an email I can contact you with?
I am making a $40 trillion bet. And I am all in.
Jensen Huang said the physical AI industry will be worth $40 trillion in the coming years. You've already seen it. The Doordash robot rolling down your street. The warehouse arm that packed your last Amazon order. This is happening. Fast.
But the teams who figure out how to train, iterate, and deploy robots quickly and cheaply? They win. Right now, most can't train, iterate on, and deploy robots QUICKLY and COST-EFFECTIVELY enough — and fall behind because of it.
And that's why we launched Cadenza CLI - the RL environment builder for physical AI infrastructure.
Our environments use abstraction to decrease redundant details in data, speeding up fine-tuning/RL processes on your physical AI projects.
→ +80% more accurate than current RL pipelines (in the same time)
→ +70% more GPU headroom per training run (reducing unnecessary compute costs)
→ Already used by robotics developers from ex-OpenAI and NVIDIA teams
Faster training. Cheaper iteration. Robots that actually ship.
If you're building in physical AI and want to move faster —> DM me. I want to hear what you're working on.
I am making a $40 trillion bet. And I am all in.
Jensen Huang said the physical AI industry will be worth $40 trillion in the coming years. You've already seen it. The Doordash robot rolling down your street. The warehouse arm that packed your last Amazon order. This is happening. Fast.
But the teams who figure out how to train, iterate, and deploy robots quickly and cheaply? They win. Right now, most can't train, iterate on, and deploy robots QUICKLY and COST-EFFECTIVELY enough — and fall behind because of it.
And that's why we launched Cadenza CLI - the RL environment builder for physical AI infrastructure.
Our environments use abstraction to decrease redundant details in data, speeding up fine-tuning/RL processes on your physical AI projects.
→ +80% more accurate than current RL pipelines (in the same time)
→ +70% more GPU headroom per training run (reducing unnecessary compute costs)
→ Already used by robotics developers from ex-OpenAI and NVIDIA teams
Faster training. Cheaper iteration. Robots that actually ship.
If you're building in physical AI and want to move faster —> DM me. I want to hear what you're working on.
working on building Cadenza's new website, as we look to make more serious partnerships with robotics labs and startups.
excited to launch our CLI soon, with dedicated RL for physical AI and infrastructure THAT LASTS.
looking forward to tomorrow!
finally, i am not broke.
during the https://t.co/kQYugQQ86u canopy festival last friday, through a mutual friend, i have reached my first EVER client.
THE BEST PART: i am going from $115 to $X.X million! THAT QUICKLY.
Cadenza helps you enter robotics QUICK. DONT MISS OUT.
finally, i am not broke.
during the https://t.co/kQYugQQ86u canopy festival last friday, through a mutual friend, i have reached my first EVER client.
THE BEST PART: i am going from $115 to $X.X million! THAT QUICKLY.
Cadenza helps you enter robotics QUICK. DONT MISS OUT.
build your robots IN MINUTES!
Cadenza SDK streamlines the process of Robotics using Python.
YOU DO NOT NEED A ROBOT, use our Mujocu-based Cadenza gym to run on your own computer!
show some love!! (and I need help, so dm if you are interested!)
https://t.co/Aw9hmf1NHu
Just reached 17 stars!!
Growing traction on the FIRST robotics SDK, removing the learning curve needed for developing in physical AI.
Attach your model and use Cadenza's action library to run your robots. AND IF YOU DON'T HAVE A ROBOT, use Cadenza's MuJoCu-native robot gym!
Just reached 17 stars!!
Growing traction on the FIRST robotics SDK, removing the learning curve needed for developing in physical AI.
Attach your model and use Cadenza's action library to run your robots. AND IF YOU DON'T HAVE A ROBOT, use Cadenza's MuJoCu-native robot gym!
Finally deployed my project on pip!
pip install cadenza-lab will install the light-weight physical AI SDK onto anyone's device.
Integrating action loops in my v1.3.2 also has improved its effectiveness in navigating complex obstacles.
very interested to see where it goes!
nobody is talking about what's next in AI.. because people are gatekeeping the next opportunity...
LLMs are plateauing, the benchmark wars are slowing down, and the next unlock isn't a smarter chatbot or b2b saas..
it's real-world impact. through robots.
machines th(Show more)
@nikillinit genuinely what has AI become 😭
I went to to Stanford last week, and as soon as I mentioned AI, I got the frown and step back from everyone around me.
its genuinely worse than brainrot atp