Atomic Machines' Matter Compiler builds micro-machines from code alone, plus engineers carrying the parts

Atomic Machines leaves stealth with a "Matter Compiler" that builds micro-machines from code

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After six years in stealth and $250M raised, the Emeryville startup showed "an AI-native manufacturing system that builds working micro-machines from code alone", with no per-product tooling and no process development: "Different code, different machine." Its first product, PrimeSwitch, is a mechanical power switch in a 9.5mm package that handles 150A and opens in 50 microseconds. @jeffholden says no semiconductor fab can process its materials or assemble its moving parts.

Sci-fi excitement, with a few noting it's MEMS so far. @DeryaTR_: "every hard sci-fi seems to be becoming reality!" @LLMJunky: "It's literally vibe manufacturing". r/accelerate's top reply: "Can it make paper clips?" A skeptic there: "mems is an established technology. this is a great commercialization of it, but nothing remotely resembling even microrobotics".

Six years for the first machine (a switch), and their site says the next ones take weeks "or days". So by their own number the second one is out before Christmas, and that's when we'll believe in the compiler (for now engineers still move the parts between its 13 machines and help put the switch together, the NYT saw it).

1. Tesla patent application for touch sensors on robot hands is published

The application describes 3D tactile sensors that conform to curved surfaces and measure force, touch and pressure, for fingertips, palms and end-effectors. Per @tslaming, the sensor is printed flat, then heat-molded around the fingers.

Read as a missing piece of the hand. @CyberRobooo: "Think of it as giving the hand a sense of touch."

Heat: medium · 112K views, 17 posts

2. [rumour] Tesla is building several hundred Optimus robots a week

Per The Information, as relayed by @tanayj: several hundred robots a week as of August, about 10x the second quarter, with a target of 1,000+ a week by year end. Hands are the bottleneck (100+ components, assembled manually), and the units stay inside Tesla for training and data collection.

Few takes. @ThematicTrader: it supports "other reports over last few weeks."

Heat: low · 12K views, 4 posts

3. Odyssey-3: a world model that also drives robots

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Odyssey's new foundation world model generates interactive environments from a prompt in real time. Its Pro version scored 66.1 on Physics-IQ Verified video-to-video (best of 8 samples), the top reported score (@DataChaz). Odyssey says the same model "powers robots", and the research preview is free.

Welcomed, and the robot results are what people kept. @omarsar0: "With tens of hours of demos, the robot arm recovered from a missed grasp, a behavior that never appeared in those demos." @aakashgupta: "physics does for world models what code did for language models."

Heat: high · 1.1M views, 51 posts

4. A humanoid punches streamer Westcol live on Kick

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While dancing with the Colombian streamer on stream, the robot hit him, then kicked through a glass display case and fell over. He carried on with the stream (@vanguardiacom). The robot is a T800 from China's EngineAI, per @Rincon001A.

A meme, mostly in Spanish. @CNviolations: the robot "attacked him out of nowhere, kicked through the display case and then proceeded to self-destruct". @binancesuperman: "they are calling it 'slapbot'".

Heat: high · 2.0M views, 20 posts

5. Aether AI shows CRIS-0, a home robot system that checks its own actions

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Aether's "first causal robotic intelligence system", shown working in a real home: it "reasons about how its actions will change the world, checks what actually happened, and adapts when reality doesn't go as expected."

Few takes so far. @clankrmedia: "In a coffee-making test, it replanned in ~2 seconds."

Heat: medium · 108K views, 3 posts

World Models' Last Exam in Physics: the best video world model scores 57.76 out of 100

Einsia tested 8 state-of-the-art video world models on 40 controlled tasks in 9 physical categories, measured against real physical laws. On free fall, the videos that passed the consistency screen averaged 26.61. It matters because robots are starting to train inside these models, and a model that gets gravity wrong teaches the wrong gravity.

PredActor: one policy that both imagines and controls a humanoid's motion

Instead of generating a motion and then tracking it, a single end-to-end diffusion policy predicts future states and outputs actions at 50 Hz onboard a Unitree G1, with text commands, joystick steering and disturbance response in the same policy. It matters because it removes the handoff between the motion a robot plans and the one it can execute.

Workhorse: whole-body humanoid skills learned from human data

On a real Unitree G1, it sorts boxes with its hands and a kick, catches a thrown box, and topples and climbs a suitcase. It matters because human data is the cheapest way to teach a humanoid to use its whole body.