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> be Sammy Azdoufal, software engineer > spend $2000 on DJI Romo vacuum > decide to control it with xbox controller like a chad > use Claude to reverse engineer the API > It works because Claude is the GOAT > just need to grab auth token from their cloud servers > token works... Claude is unbeaten > wait why is he authenticated as 7000 devices > ohno.jpg > backend trusted any valid token for any device, no ownership verification > mfw Sammy has live camera feeds from vacuums in 24 countries > watching some german dude eat cereal at 3am > can pull SLAM data and get floor plans of everyone's house > could be the world's most efficient burglar > could be the world's most at scale pervert > Sammy just wanted to drive his vacuum bro > reports it like a responsible adult > DJI patches in 2 days > back to being a normal guy with overpriced roomba > mfw the entire IoT industry treats auth like it's 2005

Thread: How China bought Germany's robotics crown jewel Quick story: I recently called Kuka German in a thread and got called out - "Kuka is Chinese now." This sent me down a rabbit hole. What I found was straight out of Succession, and it reshaped how the West thinks about tech sovereignty. This is the story of how a Chinese appliance company bought Kuka & kick-started China's robot dominance. ⬇️

WTF is this maze cast into your automatic transmission? It’s a mechanical computer that picks the right gear for you. Runs on oil, not electricity. Worked out decades before the microchip. Here’s how it works: - The inputs. Two oil pressures. One rises with road speed. One rises with how hard you press the gas. That’s all it knows: how fast am I going, and how fast do I want to go. - The job. Route oil to the right clutch so the right gear engages for what you’re asking of the car. - How it works. A spool, a small grooved cylinder, slides in a bore. Oil pushes each end; harder push wins. Speed pressure on one end, throttle plus a biasing spring on the other. Slide one way it blocks a passage, slide the other it opens one: oil floods a clutch, the clutch locks, that’s your gear. Floor it and throttle pressure shoves the spool over, drops you a gear, the car surges. Ease off and speed pressure wins, sliding it back to grab the next gear up. Two pressures, fighting it out. - Why a maze? No valve decides alone; each one’s output is another’s input. So oil has to run from every valve to the others that depend on it, and oil can’t jump gaps. Every connection needs its own channel carved in metal. Dozens of valves, hundreds of passages, none crossing where they shouldn’t - It’s a routing problem. Same one a chip designer faces: connect many things to many things without the paths colliding. They even stack plates with a drilled separator between them, like vias on a circuit board. The result: a real-time computer in aluminum and oil. Only in old-school automatics. In a manual, you’re the computer.

> be Italian Institute of Technology > decide to build a humanoid robot in 2017 > base it on a 5-year-old child > give it a terrifying doll/death mask face > name it iCub > fast forward to 2024 > “you know what this needs?” > “JETPACK” > strap four jet engines to robot toddler > achieve liftoff > “this will save people in disasters” > imagine being trapped in a flood > hear jet engines approaching > look up > it’s a flying robot toddler with a blank stare and arm mounted flamethrowers > coming to save you > or end you > can’t tell which > researchers: “it’s really cool though” > can’t argue with that > next step: coordinate with airport > because of course a flying robot baby needs airspace clearance > add wings for “efficiency” > THEY’RE MAKING IT BETTER

Another trade show demo - this time showing off how perfectly in sync these motors are. Thoughts on why you would need this level of control?

Should humanoids have tails? Current legged robots struggle with center of mass control and quick stabilization. Adding more DOF to legs gets complicated fast. Nature already solved this: Cheetahs, kangaroos, dinosaurs – they use tails for dynamic balance, sharp turns, and recovery from unexpected shifts. The robotics insight? Let the tail handle it. Virginia Tech built serpentine tails that compensate in real-time – so bipeds and quadrupeds can handle ledges, lateral shifts, and turns without rewriting their entire gait. Simple solution. Obvious in hindsight. 🦖🤖

📍 Robot localisation is the deca-billion-dollar problem no one talks about. Every mobile robot needs to know its location to within 2-5 cm. Sounds simple? It's not. Current solutions force an impossible choice: cheap but inflexible, or smart but fragile. This fundamental trade-off is blocking the mass deployment of robots. Here's why - and how nature might solve it 🧵

5-axis CNC machining – but different... Most 5-axis machines use serial kinematics: stack a rotary A-axis on top of a rotary B-axis, mount that on linear X/Y/Z stages. Each axis carries the weight of everything after it. Heavy and slow. 🤖 The Sprint Z3 uses parallel kinematics: three linear drives working together to create BOTH the Z-axis motion AND the A/B tilt simultaneously. No stacked rotary joints. No heavy tilting head carrying a motor on top of another motor. The entire barrel-shaped headstock moves as one unit vertically in the column, while the three internal drives handle the spindle positioning and orientation. ⚙️ How it works: Three linear actuators are arranged in a circle, all connected to the spindle platform through pivot arms. - Extend all three equally → spindle moves straight up/down (Z-axis) - Extend them different amounts → spindle tilts (A/B axes) It's using geometry instead of stacked rotary joints to create tilt 🤔 Why this is useful: Way less moving mass than serial kinematics. Less mass = faster accelerations, higher precision, better surface finish. For high-speed machining, dynamics matter more than workspace. Question: Is this a good design or overcomplicated❓

I feel like we’re missing the fact that Disney is building us actual droids

Traditional factory automation follows three rules: 1. Minimise degrees of freedom 2. Minimise actuation 3. Minimise the requirement for feedback Let geometry and gravity do the hard work. This is a step feeder. Reciprocating plates push parts upward, one step at a time. Parts that sit stable on the ledge rise to the top. Parts that don't? They tip off and fall back into the hopper. A chain conveyor carries the parts along and a simple tool knocks off any that are misaligned. No robot. No vision. No gripper. Just continuous circulation until every part finds its perfect orientation. Bowl feeders, gravity slides, step feeders, escapements—all built on the same principle. Constrain movement. Let shape and weight do the sorting. Modern robotics throws sensors, actuators, and computing at every problem. Sometimes the smarter move is less.

Thread: How Amazon's $775M Acquisition Accidentally Launched an Entire Industry Here's a wild story about unintended consequences: Amazon acquired a robotics company and nearly tanked the industry by removing it from the market. This seeming disaster helped catalyse a $40 billion market. Here's the story of how the Kiva acquisition sparked one of the most dynamic markets in robotics. ⬇️

Robot newbies would have used a 6-axis robot for this. Remember to use the simplest system for the job… but no simpler.

A vehicle that converts pedalling motion into steps. ✅10 points for anyone who can come up with a use case.

Thread: How China bought Germany's robotics crown jewel Quick story: I recently called Kuka German in a thread and got called out - "Kuka is Chinese now." This sent me down a rabbit hole. What I found was straight out of Succession, and it reshaped how the West thinks about tech sovereignty. This is the story of how a Chinese appliance company bought Kuka & kick-started China's robot dominance. ⬇️

Should humanoids have tails? Current legged robots struggle with center of mass control and quick stabilization. Adding more DOF to legs gets complicated fast. Nature already solved this: Cheetahs, kangaroos, dinosaurs – they use tails for dynamic balance, sharp turns, and recovery from unexpected shifts. The robotics insight? Let the tail handle it. Virginia Tech built serpentine tails that compensate in real-time – so bipeds and quadrupeds can handle ledges, lateral shifts, and turns without rewriting their entire gait. Simple solution. Obvious in hindsight. 🦖🤖

Tsubame Industries has built a 3.5-ton 'Gundam' robot exoskeleton. Priced at $3 million per system, they aim to sell systems for disaster relief or space missions. There seem to be certain designs that humans are obsessed with bringing into reality - maybe that's enough?

> be Sammy Azdoufal, software engineer > spend $2000 on DJI Romo vacuum > decide to control it with xbox controller like a chad > use Claude to reverse engineer the API > It works because Claude is the GOAT > just need to grab auth token from their cloud servers > token works... Claude is unbeaten > wait why is he authenticated as 7000 devices > ohno.jpg > backend trusted any valid token for any device, no ownership verification > mfw Sammy has live camera feeds from vacuums in 24 countries > watching some german dude eat cereal at 3am > can pull SLAM data and get floor plans of everyone's house > could be the world's most efficient burglar > could be the world's most at scale pervert > Sammy just wanted to drive his vacuum bro > reports it like a responsible adult > DJI patches in 2 days > back to being a normal guy with overpriced roomba > mfw the entire IoT industry treats auth like it's 2005

Another trade show demo - this time showing off how perfectly in sync these motors are. Thoughts on why you would need this level of control?

📍 Robot localisation is the deca-billion-dollar problem no one talks about. Every mobile robot needs to know its location to within 2-5 cm. Sounds simple? It's not. Current solutions force an impossible choice: cheap but inflexible, or smart but fragile. This fundamental trade-off is blocking the mass deployment of robots. Here's why - and how nature might solve it 🧵

> be Italian Institute of Technology > decide to build a humanoid robot in 2017 > base it on a 5-year-old child > give it a terrifying doll/death mask face > name it iCub > fast forward to 2024 > “you know what this needs?” > “JETPACK” > strap four jet engines to robot toddler > achieve liftoff > “this will save people in disasters” > imagine being trapped in a flood > hear jet engines approaching > look up > it’s a flying robot toddler with a blank stare and arm mounted flamethrowers > coming to save you > or end you > can’t tell which > researchers: “it’s really cool though” > can’t argue with that > next step: coordinate with airport > because of course a flying robot baby needs airspace clearance > add wings for “efficiency” > THEY’RE MAKING IT BETTER

5-axis CNC machining – but different... Most 5-axis machines use serial kinematics: stack a rotary A-axis on top of a rotary B-axis, mount that on linear X/Y/Z stages. Each axis carries the weight of everything after it. Heavy and slow. 🤖 The Sprint Z3 uses parallel kinematics: three linear drives working together to create BOTH the Z-axis motion AND the A/B tilt simultaneously. No stacked rotary joints. No heavy tilting head carrying a motor on top of another motor. The entire barrel-shaped headstock moves as one unit vertically in the column, while the three internal drives handle the spindle positioning and orientation. ⚙️ How it works: Three linear actuators are arranged in a circle, all connected to the spindle platform through pivot arms. - Extend all three equally → spindle moves straight up/down (Z-axis) - Extend them different amounts → spindle tilts (A/B axes) It's using geometry instead of stacked rotary joints to create tilt 🤔 Why this is useful: Way less moving mass than serial kinematics. Less mass = faster accelerations, higher precision, better surface finish. For high-speed machining, dynamics matter more than workspace. Question: Is this a good design or overcomplicated❓

Check out Robuild's autonomous construction robots They recently completed a 500 ft² LVP flooring installation, with 600 install planned by 2026. A few tech details: • Labour shortages & cost savings are driving developers to look at robotics • The system works in busy, varied houses and uses onboard vision to align and place planks without pre-mapping. • It's built on ROS, using NVIDIA Omniverse, Isaac Gym, and custom PID for precision.

WTF is this maze cast into your automatic transmission? It’s a mechanical computer that picks the right gear for you. Runs on oil, not electricity. Worked out decades before the microchip. Here’s how it works: - The inputs. Two oil pressures. One rises with road speed. One rises with how hard you press the gas. That’s all it knows: how fast am I going, and how fast do I want to go. - The job. Route oil to the right clutch so the right gear engages for what you’re asking of the car. - How it works. A spool, a small grooved cylinder, slides in a bore. Oil pushes each end; harder push wins. Speed pressure on one end, throttle plus a biasing spring on the other. Slide one way it blocks a passage, slide the other it opens one: oil floods a clutch, the clutch locks, that’s your gear. Floor it and throttle pressure shoves the spool over, drops you a gear, the car surges. Ease off and speed pressure wins, sliding it back to grab the next gear up. Two pressures, fighting it out. - Why a maze? No valve decides alone; each one’s output is another’s input. So oil has to run from every valve to the others that depend on it, and oil can’t jump gaps. Every connection needs its own channel carved in metal. Dozens of valves, hundreds of passages, none crossing where they shouldn’t - It’s a routing problem. Same one a chip designer faces: connect many things to many things without the paths colliding. They even stack plates with a drilled separator between them, like vias on a circuit board. The result: a real-time computer in aluminum and oil. Only in old-school automatics. In a manual, you’re the computer.

Here is a human assembling a BMW engine by hand. Hundreds of components. Micron tolerances. Dozens of hours. So what's better here—a human or a robot❓ 🤖 Robots win at: - Repeatability. Same torque, same angle, every time. - Speed on defined tasks. Honda automates piston installation at 9,000/day. - No fatigue. Shift 47 is identical to shift 1. 👨‍🏭 Humans win at: - Feeling what they can't see. Half of engine assembly is blind. - Force intuition. Knowing "seated" from "about to crack." - Compliant manipulation. That instinctive wiggle to get a part to drop in. - Handling variance. Mercedes pulled robots off the S-Class line because they couldn't adapt to option variability. - Deformables. Wiring harnesses, gaskets, hoses—nothing predictable. - Recovery. When something's wrong, humans adapt. Robots halt. ✅ Right now, the answer is both. Robots handle the repetitive subassemblies. Humans handle everything that requires judgment, feeling, and adaptation. The day a humanoid can do this end-to-end is the day manipulation is solved.

Even this list is missing a 10+ humanoids. Can you guess which?