Impressive hand by Pan Motor.
20 active DOFs (4 per finger), weighs <600g, 15N fingertip force, 10kg static grasp, >300,000-cycle lifespan, and 30 arcminute accuracy.
youtube.com/watch?v=LXVV-o…
First controlled test: a model trained to make coffee.
Not scripted code, but a learned policy.
Next: expand data across machines, objects & failure modes → robustness via generalization.
Coffee prep is a proxy for Physical AI: perception → action → adaptation.
#PhysicalAI
Walmart’s AI “super-agents” prove AI at scale delivers - 40% faster support, shift planning 90→30 min, fashion cycles 18 weeks shorter. That same spirit drives #PhysicalAI: machines that see, adapt & act beyond one use case.
lnkd.in/diSjqtxM
Robots with real touch? 👀
Tohoku Uni’s “TactileAloha” fuses sight + touch so bots don’t just see: they feel and adapt.
From automation → augmentation
techxplore.com/news/2025-09-p…
The Turing Test was about talking like humans.
The Barista Test is about acting in the messy real world.
For us, that means #PhysicalAI that can:
- Pick deformables w/o damage
- Adjust grip strength
- Read barcodes from odd angles
- Navigate dynamic layouts
Strong list. Physical AI as ‘the dawn’ resonates - abstract intelligence stepping into the messy, physical world is the real test.
Data centers & models are impressive, but until AI can act with the same adaptability it computes with, the revolution isn’t complete.
Strong list. Physical AI as ‘the dawn’ resonates - abstract intelligence stepping into the messy, physical world is the real test.
Data centers & models are impressive, but until AI can act with the same adaptability it computes with, the revolution isn’t complete.
We don’t just teach robots to pay attention, we teach them to act in the physical world.
In this demo, the gripper tracks a moving object by hand, adjusting in real time. No pre-scripted moves. No hard-coded paths. Just Physical AI adapting as motion happens.
Hot take: rich countries use power. Next: AI tokens vs output. High income on low tokens? That circle stays empty. In Physical AI, tokens → decisions → actions. Winners burn more per worker & robot-hour. Your tokens-per-capita: cloud, edge, or action? 🤖
Imitation Learning is the first step to #PhysicalAI.
Robots learn like we do:
👁 Watch a human act
💬 Understand the task
⚙️ Repeat & adapt in reality
From “copy me” comes the foundation of real physical intelligence.
#DeepTech#Robotics
Another day, another ‘rise of the robots’ headline. But RealSense + NVIDIA Thor actually matters: sensors that see + compute that thinks = Physical AI with less hype, more doing.
Humanoids and AMRs just got a serious upgrade.
Another day, another ‘rise of the robots’ headline. But RealSense + NVIDIA Thor actually matters: sensors that see + compute that thinks = Physical AI with less hype, more doing.
Humanoids and AMRs just got a serious upgrade.
Yes, that’s a @HariboUKI_ gummy bear.
And no, not a party trick.
This is Physical AI: vision, reasoning, and control combined so a robot can lift one of the tiniest, squishiest items straight from a human hand.
🔊 Sound on. We help robots listen, see, and act.
No scripts. No hardcoding. Just:
“Pick the orange.”
“Rotate the box.”
“Take off the lid.”
The future of Vision-Language-Action is here.
Oh look, just two robots moving in sync. Totally casual.
Not like it’s years of work in algorithms, sensors, and control packed into a 15s clip.
Sure, call it a routine test. We’ll just call it Physical AI flexing.
#AIinRobotics#PhysicalAI
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