Applied Intuition has been awarded a contract by the @USNavy to scale Data Engine across its fleet.
As the infrastructure layer for maritime autonomy, Data Engine collects operational data through passive navigation capabilities installed on Navy ships.
Here’s how the loop works:
🔵 Collect data from ships at sea
🔵 Curate it and train perception models
🔵 Evaluate the models
🔵 Deploy them back to vessels over the air
The result is what one ship learns now reaches the entire fleet – a threat encountered by a single vessel is turned into an improved model and deployed over the air, so every ship can detect it.
Our goal is for each military service to run its own Data Engine, tailored to its domain and feeding into a common infrastructure.
Learn more about our work with the U.S. Navy here:
https://t.co/YievJ6zCuf
Qasar Younis (Applied Intuition): “The fantasy that these machines that exist around us are going to be replaced by new machines just doesn’t exist”
Live from Day 2 of #LongHorizon#PhysicalAI
Everyone’s been talking about Mission S vs flying Roadsters and the physical part of their design BUT the human-machine interaction matters just as much, if not more.
Like you see and interact with your car from the inside most of the time. So then why are most in cabin experiences far from magical, seamless AI driven interactions? Because historically there wasn’t a platform to build on
When software shapes the car, what’s left for design?
The human. See how we’re building the next generation of intelligent cars with @Stellantis.
https://t.co/2NFEkVAu3K
Reinforcement Learning (RL) in simulation is a scalable strategy to learn dexterous skills, but naive exploration from scratch often fails to discover manipulation strategies for diverse objects.
At @AppliedInt, we propose X-Reset, a straightforward method to resolve the exploration problem for generalist RL policies by randomly sampling resets from human hand-object states.
- We train a single dexterous policy to manipulate a variety of objects to any goal pose, ranging from small markers to heavy powerdrills with zero teleoperation data
- The learned policy zero-shot generalizes well beyond the training set (DexYCB), and transfers from sim-to-real using object pose-tracking models
We are continuously expanding robotics research at @AppliedInt beyond X-Reset, with the bounds of simulation and synthetic data for dexterous manipulation pushed. Stay tuned and join us!
🌐 Project Page: https://t.co/xEXMnWxja2
📄 Paper: https://t.co/28Ewh0pUYS
Exploration is hard for RL when training high-DoF dex hands ✋
X-Reset makes generalist object-centric RL easier by resetting to human hand-object states 🙋♀️
We mitigate the exploration problem, and train a single policy to manipulate a variety of objects to any goal pose 🧵
“I don’t believe you can be very successful and not read a lot.”
4 books @qasar recommends, the ones that helped him build @AppliedInt, a $15B physical AI company:
📍I Am That, Sri Nisargadatta Maharaj
📍Sam Walton: Made in America, Sam Walton (with John Huey)
📍The Story of My Experiments with Truth, Mahatma Gandhi
📍Long Walk to Freedom, Nelson Mandela
Every startup says they have the best team. We looked at the data.
@paraformtalent’s Talent Density Index ranks which companies attract, develop and retain the people the market values most.
The latest edition is live.
New Top 50: https://t.co/KoZ5BPpnY8
Not 1 but 2 mega announcements to share!
#1: We’re partnering with Honda to build the software platform powering their next-generation of AI-defined vehicles.
https://t.co/6v41Vdv5Mq
Silicon Valley software expertise x Japanese engineering excellence.
Applied Intuition and @HondaJP are partnering to speed up Honda’s in-house development of a centralized, upgradeable SDV platform.
Learn more about how we are working together to transform the automotive industry.
https://t.co/5nOqFvFEHG
AI-defined vehicles require transforming more than the software in the car, they require transforming how that software gets built.
That’s why we’re excited to partner with @Nissan to support their next-gen SDV and AI-defined vehicle efforts, built on our Vehicle OS.
This is how AI-defined vehicles get built from here.
https://t.co/KoRGIgR4xd
Our team is headed to @Stanford this Wednesday, October 7th, for the Stanford Computer Forum Career Fair!
Drop by McCaw Hall at the Arrillaga Alumni Center between 11am and 4pm to meet our team and learn about how our team is solving the most complex challenges in physical AI.
https://t.co/PDZsdpKSyR