Applied Intuition is the physical AI company bringing intelligence to every moving machine on the planet.
Sunnyvale, CA
Joined August 2017
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Excited to rank #12 on this year’s @NewcomerMedia AI 100 list. So proud of the work of our talented team.
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Our CEO and co-founder, @qasar recently shared his takes on how to build a successful company.
Why do most founders fail?
@qasar has built three companies, including @AppliedInt. His answer: they misread their users’ feedback.
It’s not about how long or how hard you work.
As cars become more and more intelligent, the cabin could one day adapt to every driver.
So how do you keep a Jeep feeling like a Jeep?
@Stellantis’ Chief Design Officer Ralph Gilles and our Head of Design and Marketing Karl Heiselman talk brand identity in the era of AI.
appliedintuition.com/blog/st…
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How we work matters as much as what we build. For @malharhar, that starts with radical pragmatism.
Learn more about his experience over the years: review.firstround.com/firsth…
End-to-end driving doesn’t need human demonstrations.
At millions of steps per second, self-play produces the collisions, near-misses and recoveries that no driving log contains. TerraTransfer++, the latest in our Terra Series, distills that experience into a camera-only planner that outperforms every published method on NAVSIM navtest and navhard:
➡️ 59.4 EPDMS on NAVSIM navhard, ahead of DriveZero-Scale (57.1)
➡️ 95.5 PDMS on NAVSIM navtest
➡️ 0.548 closed-loop HD-Score on HUGSim
Paper: arxiv.org/abs/2610.30319
Project: terra-applied.github.io/Terr…
Applied Intuition retweeted
“The fantasy that these machines that exist around us are all going to be replaced by new machines. This just doesn’t exist.” - @qasar, CEO of @AppliedInt
Qasar’s argument is that the real work in physical AI is retrofitting the billion machines already on the planet. A consumer car runs for 15 years, construction and mining equipment for 30, and defense hardware for six decades, so most of the world’s machines will get their intelligence added, not built in.
Applied Intuition retweeted
I know it feels like a really competitive market, but Physical AI is not a zero-sum game.
@AppliedInt CTO Peter Ludwig looked out at 200 founders at Dirty Jobs this year and said every one of them can win, because the markets we build in are really THAT big.
He explained why we're seeing an explosion in interest across autonomy "Reinforcement Learning only got fast enough to matter in the last 12 to 18 months"
The time is now. EP 104 of CLIMB 👇
Applied Intuition retweeted
[New Blog] How does labeled data become a model back on the road? 🔄 At @AppliedInt, our physical AI data flywheel runs over hundreds of petabytes. Here's how: appliedintuition.com/enginee…
🎤 At @lancedb's #Reverie2026 on Nov. 5th? Catch my talk on the main stage, 11:30 AM PT.
How does labeled data become a model back on the road?
@_xushiyan breaks down each stage: curation, scenarios, data loading, training, and evaluation, across hundreds of petabytes of multimodal data.
appliedintuition.com/enginee…
Catch him on the main stage at LanceDB's #Reverie2026, Nov. 5th at 11:30 AM PT.
Applied Intuition retweeted
Can we achieve state-of-the-art for mainstream E2E and vectorized driving benchmarks without using any human demonstration data?
Terra series at @AppliedInt now tops the NAVSIM, HUGSim, nuPlan val14 and InterPlan benchmarks, powered by self-play RL without imitation, scaling in closed loop with all agents being reactive.
🚘 With TerraZero released a few months ago, we set the SOTA on vectorized benchmarks like nuPlan val14 and InterPlan, powered by our super high-throughput self-play RL framework experiencing 25 centuries of challenging driving scenarios.
📽️ In June this year, TerraTransfer was released as the first of its kind to bring the SOTA vectorized policy from self play (TerraZero) to an E2E policy via image-to-vector encoder alignment, which topped the HUGSim closed-loop score.
🔚 This week, we are thrilled to release TerraTransfer++, a demonstration-free E2E planner setting the SOTA for NAVSIM and HUGSim, by adding planning capability from self-play rollout experience to TerraTransfer.
Setting SOTA for public benchmarks is just a beginning, as we have seen the journey from pioneering work like UniAD to successful mass production of E2E ADAS in the industry, but what makes me quite excited is to see the strong signal from a new paradigm with potential to refactorize how the next generation autonomy can be developed, and bring the scalability, safety and performance to the next level.
We are the believer of data and scaling, but not just human demonstration data and open-loop scaling like imitation or open-loop RL (AV2.0) - we have the bet on closed-loop scaling with both synthetic and real-world data (AV3.0), and the Terra series is the starting point of the journey towards real product with our bet.
Great work from the team @caffe_tt, Weixin Li, Zhouchonghao Wu, @AkshayRangesh, Saarth Bonde, Grantland Hall, @ChenTangMark, Yihan Hu, for creating TerraTransfer and TerraTransfer++!
TerraTransfer++ report: arxiv.org/abs/2610.30319
TerraTransfer++ website: terra-applied.github.io/Terr…
TerraTransfer report: arxiv.org/abs/2606.17386
Then we teach it to see. Adapters on a frozen DINOv3 backbone align camera features to the frozen teacher’s latent space.
Every target traces back to self-play, so training needs only paired (image, scene-state) frames. No expert trajectories, no online rendering.
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The key move: decouple learning to drive and plan from learning to see.
Self-play in a vectorized sim runs at millions of steps/s and naturally covers collisions, near-misses and recoveries. We distill those rollouts into a flow-matching trajectory planner.
E2E driving is bottlenecked by data. Imitation needs fleet-scale logs that barely cover the safety-critical long tail. Closed-loop RL in photoreal sim pays per-step rendering and backbone cost.
TerraTransfer++ removes human demonstrations from every stage and achieves state-of-the-art driving performance across open-loop and closed-loop benchmarks. 🧵
Paper: arxiv.org/abs/2610.30319
Website: terra-applied.github.io/Terr…
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:
appliedintuition.com/blog/na…
Applied Intuition retweeted
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
Where does physical AI go from here? @qasar shares his takes with @eostudi0.
Watch the full episode: youtu.be/REsrgNeuZkU
🤖 Made with AI
Applied Intuition retweeted
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.
appliedintuition.com/blog/st…
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.
appliedintuition.com/blog/st…
Applied Intuition retweeted
Simulation is still our bread and butter and it’s only becoming clearer that it’ll unlock robotics at scale
