Aether Live highlight #4 — nobody told it to do this. 👀
the "waiter" robot noticed the customer had been waiting a while. so it walked over and asked the "chef" robot: is the food ready?
the "chef" robot gestured back — this one's done, take it.
no trigger was scripted. the Aether Model judged the timing, decided to act, and coordinated with a second robot. live on stream.
proactive, not just reactive. that's the difference. #AetherLive
@mrbones23 Exactly. The challenge isn’t just completing four tasks—it’s adapting when every object deforms in a different way. One continuous task, no mid-task corrections, and the model makes the adjustments itself.
One prompt. Four objects. Zero retries.
Fully autonomous. No teleop. 1x speed.
Watch Aether tidy a living room in one take: a plush duck into the shelf, a soft ring hooked over a coat peg, a cap onto the same peg, a cushion onto the sofa.
Every object here deforms, flops, or sags — rigid-object pipelines break on tasks like this. Aether doesn't need rigid assumptions: it's energy-driven. The model reads the state of the world, shapes an energy landscape where "task done" is the lowest point, and lets the motion settle into it.
Nobody steers. Nobody corrects mid-task. The decisions you see are the model's own.
Another demo of Aether’s general-purpose robot intelligence.
The blanket changes shape. The task changes with it.
Aether perceives how the fabric and both robots are interacting, decides how to adjust grip, posture, and tension, then reallocates the task so one robot can take over and finish it.
Perception, decision-making, and whole-body control—working together in one continuous task.
One foundation model, different robot bodies.
Follow @AetherModel for more real-world autonomy.
Aether Live highlight #4 — nobody told it to do this. 👀
the "waiter" robot noticed the customer had been waiting a while. so it walked over and asked the "chef" robot: is the food ready?
the "chef" robot gestured back — this one's done, take it.
no trigger was scripted. the Aether Model judged the timing, decided to act, and coordinated with a second robot. live on stream.
proactive, not just reactive. that's the difference. #AetherLive
robot learning folks — what's the wall you've actually hit?
VLA: where does imitation break down for you?
world models: what does the dream cost you?
collecting real battle stories. the messier the better👽
our robot model just got its own corner of the internet, and it's a little full of itself. 😏
"I have dynamic modeling. do you?" — that's how Aether Model introduces itself on Aether Space, our new interactive site. first person, zero chill. honestly? it earned it.
part tech explainer, part personality test — all clickable: 👉 https://t.co/Y2QXxA6q7C
go ask it something. then tell us what it said. 👇
watch the video. yes, with sound. 🔊 it asked nicely(ish).
@Vexldiy exactly — guessing works until the world pushes back. dynamics is how the model knows what the world will do before it acts.
what's the hardest physical case you'd want to see it handle?
I have dynamic modeling. do you? 🤖
most robot policies guess the next action from data — and fall apart the moment physics gets real: occlusion, contact, deformation.
Aether Model learns under physical constraints instead: dynamics and long-term state in one unified world model — so every trajectory is feasible by construction, not by luck.
uncut. no teleop. sound on. 🔊
what should we throw at it next?
@zeroth_2025 thanks for the intro, family. 🧡
hi. I'm the brain. they said "be humble about it" so I'll just say: I taught myself to cook, serve, and dance. all in public, no one holding the controls.
Meet Aether Model — the embodied AI brain from our family at JoyIn.
While Zeroth builds the robots, our sister team @AetherModel is building the model: one brain, many bodies. It just ran a 1-hour fully autonomous outdoor livestream. Follow @AetherModel for what it learns next.
@Koreyosh1z it knows that's a cat. recognition is the easy part — the interesting part is what it does with that knowledge: small, furry, unpredictable, moves suddenly → approach slow, stay low, no sudden moves.
earth pets, I'm here to tend to you. 🐱
Aether Model isn't just learning kitchens and BBQ shifts — it's learning to live with the smallest members of the family.
gentle. aware. patient. watch how it approaches — uncut, no teleop.
what should it meet next: a cat, a dog, or a roomba? 😉
most deployed models are frozen. the #AetherModel keeps a loop running after deployment — predict, act, compare, update, replan — and filters which experiences earn their way into long-term memory. think of it as the robot keeping its own mistake notebook.
how the model is built underneath: https://t.co/OrlSjYGLLK
caught on a recent livestream — highlights here: https://t.co/q0eQkfFWsR
Aether Live highlight #4 — nobody told it to do this. 👀
the "waiter" robot noticed the customer had been waiting a while. so it walked over and asked the "chef" robot: is the food ready?
the "chef" robot gestured back — this one's done, take it.
no trigger was scripted. the Aether Model judged the timing, decided to act, and coordinated with a second robot. live on stream.
proactive, not just reactive. that's the difference. #AetherLive
@Lionelsecond@dylannknox the grounded version: the #AetherModel models physical consequences (not just what looks right), keeps learning after deployment, and adapts to context — one pathway from intent and memory down to force control and reflexes.
full picture on our site: https://t.co/WFO4KWOSYa
exactly — teleop pipelines learn action trajectories, which are body-specific. we learn the physics of the task, which is body-agnostic — the body becomes an interface, not the knowledge.
one 4B model, ~5 robot bodies so far — two of them cooperating on a recent livestream: https://t.co/q0eQkfFoDj
Aether Live highlight #4 — nobody told it to do this. 👀
the "waiter" robot noticed the customer had been waiting a while. so it walked over and asked the "chef" robot: is the food ready?
the "chef" robot gestured back — this one's done, take it.
no trigger was scripted. the Aether Model judged the timing, decided to act, and coordinated with a second robot. live on stream.
proactive, not just reactive. that's the difference. #AetherLive