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Ilir Aliu

@IlirAliu_ • 54,742 subscribers

Building @22Astronauts_ The studio for European Physical AI. Writing Signal at https://t.co/9Nm01QUcw3

Shorts

This was 25 years ago. I often think about that.

This was 25 years ago. I often think about that.

121,239 views

You don’t need expensive hardware to build something that feels like real robotics. An Arduino, a servo, and an ultrasonic sensor can scan space and turn echoes into a simple radar view. It sweeps, measures distance, and visualizes it in real time. Cheap, simple, and a solid way to understand how machines sense the world. Limits show up fast, which is where better sensing and smarter software come in. Original build by SunFounder —— Weekly robotics and AI insights. Subscribe free:

You don’t need expensive hardware to build something that feels like real robotics. An Arduino, a servo, and an ultrasonic sensor can scan space and turn echoes into a simple radar view. It sweeps, measures distance, and visualizes it in real time. Cheap, simple, and a solid way to understand how machines sense the world. Limits show up fast, which is where better sensing and smarter software come in. Original build by SunFounder —— Weekly robotics and AI insights. Subscribe free:

874,948 views

AI in robotics gets all the attention right now, but sometimes the most interesting work is very practical. Viet built a small vision system that counts potatoes on a conveyor belt. No giant dataset. No huge model. Just a clear problem and a smart setup. He used Ultralytics’ ObjectCounter, trained a tiny YOLO11 nano model, and because there was no potato dataset, he annotated a single frame with SAM 2 and trained from that. One frame. Still works across the whole video. It is a good reminder that useful AI in industry often looks like this. Focused. Lightweight. Solves a real task. If you work in manufacturing or robotics, these small systems are usually the fastest wins. They save time, reduce errors, and do not need massive infrastructure. Nice work, Viet. His projects: —- Weekly robotics and AI insights. Subscribe free:

AI in robotics gets all the attention right now, but sometimes the most interesting work is very practical. Viet built a small vision system that counts potatoes on a conveyor belt. No giant dataset. No huge model. Just a clear problem and a smart setup. He used Ultralytics’ ObjectCounter, trained a tiny YOLO11 nano model, and because there was no potato dataset, he annotated a single frame with SAM 2 and trained from that. One frame. Still works across the whole video. It is a good reminder that useful AI in industry often looks like this. Focused. Lightweight. Solves a real task. If you work in manufacturing or robotics, these small systems are usually the fastest wins. They save time, reduce errors, and do not need massive infrastructure. Nice work, Viet. His projects: —- Weekly robotics and AI insights. Subscribe free:

1,676,696 views

A student built a real anti-gravity machine… using an Arduino. How to Make an Acoustic Levitator: Arduino Nano + motor driver + about 60 ultrasonic transducers. They all emit ~40 kHz sound. The sound waves meet and form fixed pockets in the air. Tiny bits of styrofoam get stuck in those pockets and just hang there. If you put your hand in, the pattern breaks and they fall. Same principle labs use to move droplets or samples without touching them. Credit: u/williamlk5341 on r/arduino Based on an “Acoustic Levitator” Instructable guide: ---- Weekly robotics and AI insights. Subscribe free:

A student built a real anti-gravity machine… using an Arduino. How to Make an Acoustic Levitator: Arduino Nano + motor driver + about 60 ultrasonic transducers. They all emit ~40 kHz sound. The sound waves meet and form fixed pockets in the air. Tiny bits of styrofoam get stuck in those pockets and just hang there. If you put your hand in, the pattern breaks and they fall. Same principle labs use to move droplets or samples without touching them. Credit: u/williamlk5341 on r/arduino Based on an “Acoustic Levitator” Instructable guide: ---- Weekly robotics and AI insights. Subscribe free:

818,367 views

Why add sensors and complex systems when physics can do the job? This production line sorts products using only weight and controlled bursts of air. ✅ No cameras or vision models ✅ No expensive integration ✅ Just reliable, repeatable separation at scale It’s a reminder that not every automation breakthrough is about AI or advanced robotics... sometimes simple mechanical principles are the most efficient solution. —- Weekly robotics and AI insights. Subscribe free:

Why add sensors and complex systems when physics can do the job? This production line sorts products using only weight and controlled bursts of air. ✅ No cameras or vision models ✅ No expensive integration ✅ Just reliable, repeatable separation at scale It’s a reminder that not every automation breakthrough is about AI or advanced robotics... sometimes simple mechanical principles are the most efficient solution. —- Weekly robotics and AI insights. Subscribe free:

532,401 views

The most interesting part of this robot is not the arm. It is the gripper. Instead of pushing the whole robot faster, this setup adds speed at the end effector. The gripper itself becomes a moving axis that can accelerate independently of the arm. That changes the physics of the system. • Faster cycle times without stressing the robot structure • Less inertia to fight against • Motion where it actually matters, at the tool center point It is a reminder that many performance limits in robotics are not solved by bigger motors, but by smarter mechanics. ——- Weekly robotics and AI insights. Subscribe free:

The most interesting part of this robot is not the arm. It is the gripper. Instead of pushing the whole robot faster, this setup adds speed at the end effector. The gripper itself becomes a moving axis that can accelerate independently of the arm. That changes the physics of the system. • Faster cycle times without stressing the robot structure • Less inertia to fight against • Motion where it actually matters, at the tool center point It is a reminder that many performance limits in robotics are not solved by bigger motors, but by smarter mechanics. ——- Weekly robotics and AI insights. Subscribe free:

46,721 views

Hardware Production 🤝 Robotics But these motors... are CRAZY synced: CNC motor synchronization helps make sure that different motors in a machine work together smoothly so that the machine can cut and shape materials with perfect accuracy. This is really important for making sure the machine does its job correctly. ✅ Helps the machine's parts move together perfectly, reducing mistakes and making things more accurate. ✅ Prevents the machine from getting damaged by keeping everything aligned. ✅ Allows the machine to work faster by making sure the motors are in sync. Synchronized CNC motors make sure machines work better, last longer, and create more precise products. —- Weekly robotics and AI insights. Subscribe free:

Hardware Production 🤝 Robotics But these motors... are CRAZY synced: CNC motor synchronization helps make sure that different motors in a machine work together smoothly so that the machine can cut and shape materials with perfect accuracy. This is really important for making sure the machine does its job correctly. ✅ Helps the machine's parts move together perfectly, reducing mistakes and making things more accurate. ✅ Prevents the machine from getting damaged by keeping everything aligned. ✅ Allows the machine to work faster by making sure the motors are in sync. Synchronized CNC motors make sure machines work better, last longer, and create more precise products. —- Weekly robotics and AI insights. Subscribe free:

317,920 views

$1,000,000,000+ raised... How can a guy from a tiny town in Illinois, with no engineering degree, be the one building the most powerful humanoid company in the world? The story makes no sense. Until it does. [Long Thread 🧵]

$1,000,000,000+ raised... How can a guy from a tiny town in Illinois, with no engineering degree, be the one building the most powerful humanoid company in the world? The story makes no sense. Until it does. [Long Thread 🧵]

313,752 views

XYZ: Let’s build a humanoid company to save humanity from the labour shortage Meanwhile:

XYZ: Let’s build a humanoid company to save humanity from the labour shortage Meanwhile:

263,792 views

America and China build robots. Europe builds committees. Tesla just showed Optimus in pilot production. Humanoids being assembled like cars. Meanwhile, in Europe, we’re still arguing over regulation, ethics boards, and frameworks that nobody in the real world reads. This isn’t about copying the US. It’s about realizing that if we keep optimizing for safety over progress, we’ll end up safe... but irrelevant. I work in robotics companies every day. We have world-class talent here... But talent without permission to execute is just potential wasted. —- Weekly robotics and AI insights. Subscribe free:

America and China build robots. Europe builds committees. Tesla just showed Optimus in pilot production. Humanoids being assembled like cars. Meanwhile, in Europe, we’re still arguing over regulation, ethics boards, and frameworks that nobody in the real world reads. This isn’t about copying the US. It’s about realizing that if we keep optimizing for safety over progress, we’ll end up safe... but irrelevant. I work in robotics companies every day. We have world-class talent here... But talent without permission to execute is just potential wasted. —- Weekly robotics and AI insights. Subscribe free:

184,088 views

The uncomfortable truth in robotics: Better tech does not win. Execution does. A small French team raised $20M and deployed in 100+ factories with ZERO hardware or manufacturing background. Here is how they did it 👇 [If you build robotics, save this thread. 🧵]

The uncomfortable truth in robotics: Better tech does not win. Execution does. A small French team raised $20M and deployed in 100+ factories with ZERO hardware or manufacturing background. Here is how they did it 👇 [If you build robotics, save this thread. 🧵]

153,085 views

For 41 years, to find shortest paths in a graph, the Dijkstra’s algorithm, was seen as the best possible way. Not any longer: Now a team from Tsinghua University has beaten it. They created the first faster algorithm for directed shortest paths since 1984. • Faster than Dijkstra on large sparse graphs • Works with real, non-negative edge weights • Proves that sorting is not the main bottleneck anymore Shortest-path algorithms power maps, GPS, logistics, networking, and robotics. This result shows that even the most “finished” algorithms can still be improved. Thanks for sharing, Md Ismail Šojal 🕷️! 📍 Paper: —— Weekly robotics and AI insights. Subscribe free:

For 41 years, to find shortest paths in a graph, the Dijkstra’s algorithm, was seen as the best possible way. Not any longer: Now a team from Tsinghua University has beaten it. They created the first faster algorithm for directed shortest paths since 1984. • Faster than Dijkstra on large sparse graphs • Works with real, non-negative edge weights • Proves that sorting is not the main bottleneck anymore Shortest-path algorithms power maps, GPS, logistics, networking, and robotics. This result shows that even the most “finished” algorithms can still be improved. Thanks for sharing, Md Ismail Šojal 🕷️! 📍 Paper: —— Weekly robotics and AI insights. Subscribe free:

95,270 views

Robots can now reconstruct 3D scenes in real time from a single RGB camera. [📍 Projects page + paper] No depth sensor. No retraining. 30 FPS. Researchers at the Imperial College London introduced KV-Tracker, a training-free method that makes heavy models like π³ and Depth Anything 3 fast enough for real-time tracking. The idea is simple. These models use global self-attention, which is powerful but computationally expensive. KV-Tracker caches the key and value pairs from selected keyframes and reuses them for new frames. That cache becomes an implicit scene representation. Result: • Up to 30 FPS • 10 to 15x speedup • Accurate 6-DoF tracking on benchmarks like TUM RGB-D and 7-Scenes • Works with monocular RGB only It also supports object-level tracking with masks and allows saving the KV-cache for later reuse. For robotics, this reduces hardware constraints and moves real-time 3D perception closer to practical deployment. Credit to Marwan Taher (Marwan Taher) at Imperial’s Dyson Robotics Lab and many others who contributed to this! 📍 Save projects page + paper for later: Video: ——- if it matters in AI or Robotics you'll read it here first:

Robots can now reconstruct 3D scenes in real time from a single RGB camera. [📍 Projects page + paper] No depth sensor. No retraining. 30 FPS. Researchers at the Imperial College London introduced KV-Tracker, a training-free method that makes heavy models like π³ and Depth Anything 3 fast enough for real-time tracking. The idea is simple. These models use global self-attention, which is powerful but computationally expensive. KV-Tracker caches the key and value pairs from selected keyframes and reuses them for new frames. That cache becomes an implicit scene representation. Result: • Up to 30 FPS • 10 to 15x speedup • Accurate 6-DoF tracking on benchmarks like TUM RGB-D and 7-Scenes • Works with monocular RGB only It also supports object-level tracking with masks and allows saving the KV-cache for later reuse. For robotics, this reduces hardware constraints and moves real-time 3D perception closer to practical deployment. Credit to Marwan Taher (Marwan Taher) at Imperial’s Dyson Robotics Lab and many others who contributed to this! 📍 Save projects page + paper for later: Video: ——- if it matters in AI or Robotics you'll read it here first:

53,992 views

It doesn’t look like much. But this small robot from Stanford might do for robotics what the Apple II did for computing... make it personal. 🧵 [📍 Save this... you’ll want to remember his name.]

It doesn’t look like much. But this small robot from Stanford might do for robotics what the Apple II did for computing... make it personal. 🧵 [📍 Save this... you’ll want to remember his name.]

91,480 views

Everyone: automation is boring. Me:

Everyone: automation is boring. Me:

88,100 views

This. Is. Open. Source.

This. Is. Open. Source.

54,783 views

A drone that flies, drives, and switches modes in 0.1 seconds: [Build it yourself: CAD + parts ⬇️] No extra actuators, no deformation, just clever mechanics and full control. DUAWLFIN is a ground-aerial robot with unified actuation: flying like a quadcopter, rolling like a car, and transitioning seamlessly between modes. ✅ Climbs 30° slopes ✅ Hits 2 m/s on wheels with just 15W ✅ Only 3% added energy in flight mode ✅ Mode switch in 0.1s ✅ Fully open-source and 3D-printable Perfect for urban logistics, indoor nav, or just rethinking what drones can be. Paper: Website: Build it yourself: CAD + parts list in the paper 📍 BOOKMARK FOR LATER This is how you merge air and ground without compromise. —- Weekly robotics and AI insights. Subscribe free:

A drone that flies, drives, and switches modes in 0.1 seconds: [Build it yourself: CAD + parts ⬇️] No extra actuators, no deformation, just clever mechanics and full control. DUAWLFIN is a ground-aerial robot with unified actuation: flying like a quadcopter, rolling like a car, and transitioning seamlessly between modes. ✅ Climbs 30° slopes ✅ Hits 2 m/s on wheels with just 15W ✅ Only 3% added energy in flight mode ✅ Mode switch in 0.1s ✅ Fully open-source and 3D-printable Perfect for urban logistics, indoor nav, or just rethinking what drones can be. Paper: Website: Build it yourself: CAD + parts list in the paper 📍 BOOKMARK FOR LATER This is how you merge air and ground without compromise. —- Weekly robotics and AI insights. Subscribe free:

69,193 views

Robotics keeps hitting the same wall. Single task RL works, but... it does not scale to hundreds of tasks or new embodiments. This new paper looks like a real step toward fixing that. The team introduces MMBench, a benchmark with 200 tasks across many domains and robots, and Newt, a language conditioned world model trained online across all 200 tasks at once. The simple idea behind Newt: The model learns from demos to get the right priors It trains across many tasks through online interaction It uses language to ground the goal It adapts fast when a new task shows up What stood out to me: ✅ One model trained on 200 tasks at the same time ✅ Language conditioned control for both states and RGB ✅ Better data efficiency than strong baselines ✅ Strong open loop control ✅ Fast adaptation to new tasks and embodiments ✅ Full release of 200 checkpoints, 4000 demos, code, and benchmark This is a good push toward general control instead of one model per task. If you want the full paper: Project page: —- Weekly robotics and AI insights. Subscribe free:

Robotics keeps hitting the same wall. Single task RL works, but... it does not scale to hundreds of tasks or new embodiments. This new paper looks like a real step toward fixing that. The team introduces MMBench, a benchmark with 200 tasks across many domains and robots, and Newt, a language conditioned world model trained online across all 200 tasks at once. The simple idea behind Newt: The model learns from demos to get the right priors It trains across many tasks through online interaction It uses language to ground the goal It adapts fast when a new task shows up What stood out to me: ✅ One model trained on 200 tasks at the same time ✅ Language conditioned control for both states and RGB ✅ Better data efficiency than strong baselines ✅ Strong open loop control ✅ Fast adaptation to new tasks and embodiments ✅ Full release of 200 checkpoints, 4000 demos, code, and benchmark This is a good push toward general control instead of one model per task. If you want the full paper: Project page: —- Weekly robotics and AI insights. Subscribe free:

70,090 views

Mini 6 dof Arm. 3D printed planetary gearboxs & more… [📍GitHub link below ] A mini 6-axis arm driven by stepper motors with custom 3D printed split ring planetary gearboxs and an inverted belt differential wrist with custom bearings, driven by low-cost stepper motors and TMC5150 drivers. Custom firmware was written in C for the STM32 MCU on an BTT Octopus board, to allow for full closed loop PID control using AS5048a encoders daisy-chained over SPI. The controller takes joint targets and returns joint states to a Raspberry Pi 5 streamed over CAN bus. All credit to James Gullberg: 📍GitHub: —— Weekly robotics and AI insights. Subscribe free:

Mini 6 dof Arm. 3D printed planetary gearboxs & more… [📍GitHub link below ] A mini 6-axis arm driven by stepper motors with custom 3D printed split ring planetary gearboxs and an inverted belt differential wrist with custom bearings, driven by low-cost stepper motors and TMC5150 drivers. Custom firmware was written in C for the STM32 MCU on an BTT Octopus board, to allow for full closed loop PID control using AS5048a encoders daisy-chained over SPI. The controller takes joint targets and returns joint states to a Raspberry Pi 5 streamed over CAN bus. All credit to James Gullberg: 📍GitHub: —— Weekly robotics and AI insights. Subscribe free:

33,958 views

Open-Source Multi-Sensor Data Platform for Neural 3D Reconstruction and Physical AI [📍github] It handles cameras, LiDAR, radar, poses, calibrations & labels in one clean format. No more messy custom parsers. • Super efficient (non-redundant storage) • New .itar single-file format with lightning-fast random access • Streams straight from S3/GCS/Azure – perfect for huge datasets • Built-in converters for Waymo, ScanNet++ & more • Already powers NVIDIA NuRec, 3DGRUT & gsplat Saw this at Janick Martinez Esturo, thanks for sharing! Easy to try: • pip install nvidia-ncore • GitHub: • Docs & project page: NCore slashes data wrangling time, cuts storage waste, and makes large-scale neural 3D training faster and simpler than ever. A real standard for physical AI. ——- Weekly robotics and AI insights. Subscribe free:

Open-Source Multi-Sensor Data Platform for Neural 3D Reconstruction and Physical AI [📍github] It handles cameras, LiDAR, radar, poses, calibrations & labels in one clean format. No more messy custom parsers. • Super efficient (non-redundant storage) • New .itar single-file format with lightning-fast random access • Streams straight from S3/GCS/Azure – perfect for huge datasets • Built-in converters for Waymo, ScanNet++ & more • Already powers NVIDIA NuRec, 3DGRUT & gsplat Saw this at Janick Martinez Esturo, thanks for sharing! Easy to try: • pip install nvidia-ncore • GitHub: • Docs & project page: NCore slashes data wrangling time, cuts storage waste, and makes large-scale neural 3D training faster and simpler than ever. A real standard for physical AI. ——- Weekly robotics and AI insights. Subscribe free:

32,717 views

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Robotics companies: let us solve repetitive tasks like folding shirts. Meanwhile, the factory floor:
2:59
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Robotics companies: let us solve repetitive tasks like folding shirts. Meanwhile, the factory floor:

Ilir Aliu

1,657,457 views • 3 months ago

Everyone talks about humanoids. Meanwhile, Loki Robotics:
1:29
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Everyone talks about humanoids. Meanwhile, Loki Robotics:

Ilir Aliu

3,280,903 views • 6 months ago

Forget lidar. One single camera. Runs in real time & is open source: A streaming 3D model that reconstructs scenes live, at ~20 FPS, over long sequences. End-to-end. Optimization tricks, cleanup steps? Nope. And it beats both streaming and even some offline methods. Perception is becoming software-first. Closer to machines that see and understand the world as it unfolds. Thanks for sharing, Yinghao Xu 📍Models: Project page: Code: Paper: —— Weekly robotics and AI insights. Subscribe free:
3:30
IlirAliu_'s profile picture

Forget lidar. One single camera. Runs in real time & is open source: A streaming 3D model that reconstructs scenes live, at ~20 FPS, over long sequences. End-to-end. Optimization tricks, cleanup steps? Nope. And it beats both streaming and even some offline methods. Perception is becoming software-first. Closer to machines that see and understand the world as it unfolds. Thanks for sharing, Yinghao Xu 📍Models: Project page: Code: Paper: —— Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

593,620 views • 2 months ago

You need $100 Billion to solve self-driving? Wrong. A small team of engineers in San Diego is doing it with a smartphone chip and a few cameras: ... for $999.🧵
0:44
IlirAliu_'s profile picture

You need $100 Billion to solve self-driving? Wrong. A small team of engineers in San Diego is doing it with a smartphone chip and a few cameras: ... for $999.🧵

Ilir Aliu

1,525,412 views • 8 months ago

Just look at these systems from CPS... they show what hyper-optimized automation actually looks like. Product arrives flat, a racetrack mechanism flips it upright, rows get grouped, and a bomb-door system drops the whole batch into the case. Fast, reliable, and dead simple. I don't see any serious humanoid adoption on the shop floor. Purpose-built machinery keep winning the speed and cost debate... at least for some more time to come. Packing flexible bags into cases looks easy until you try doing it at scale across different pouch formats. Seeing setups like this always brings up two questions for me. First, how does a flashy humanoid like Figure actually compare to a dedicated machine like this in the real world? Humanoids get all the media attention, but when it comes to raw throughput, uptime, and ROI on a specific packaging line, specialized kinematics usually wipe the floor with general-purpose robots. Second, how long until European regulations try to over-engineer safety or compliance rules around setups like this? While engineers are trying to innovate and speed up factory floors, we seem remarkably good at inventing new regulatory hurdles that slow down deployment across Europe. I’m curious how people who are working in those startups, packaging and industrial automation view this situation.
0:32
IlirAliu_'s profile picture

Just look at these systems from CPS... they show what hyper-optimized automation actually looks like. Product arrives flat, a racetrack mechanism flips it upright, rows get grouped, and a bomb-door system drops the whole batch into the case. Fast, reliable, and dead simple. I don't see any serious humanoid adoption on the shop floor. Purpose-built machinery keep winning the speed and cost debate... at least for some more time to come. Packing flexible bags into cases looks easy until you try doing it at scale across different pouch formats. Seeing setups like this always brings up two questions for me. First, how does a flashy humanoid like Figure actually compare to a dedicated machine like this in the real world? Humanoids get all the media attention, but when it comes to raw throughput, uptime, and ROI on a specific packaging line, specialized kinematics usually wipe the floor with general-purpose robots. Second, how long until European regulations try to over-engineer safety or compliance rules around setups like this? While engineers are trying to innovate and speed up factory floors, we seem remarkably good at inventing new regulatory hurdles that slow down deployment across Europe. I’m curious how people who are working in those startups, packaging and industrial automation view this situation.

Ilir Aliu

56,157 views • 10 days ago

KoalaLifter... A robot to fix wind turbines Quite interesting, with an autonomous crane system ⁉️ Wind energy is a crucial renewable energy source This solution might help: > Erect turbine and replace spare parts without a crane > No height limits, no wind speed limits > More robust, reliable and safer You gotta like those innovations! Featured: KoalaLifter, GiGadgets,
1:29
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KoalaLifter... A robot to fix wind turbines Quite interesting, with an autonomous crane system ⁉️ Wind energy is a crucial renewable energy source This solution might help: > Erect turbine and replace spare parts without a crane > No height limits, no wind speed limits > More robust, reliable and safer You gotta like those innovations! Featured: KoalaLifter, GiGadgets,

Ilir Aliu

161,541 views • 1 month ago

Every robot you see is a data firehose generating terabytes of chaos. This hidden crisis is the #1 reason robots fail, and it's costing the industry billions. You see hardware, but not the data swamp drowning engineers. In 2025, a quiet revolution is fixing it. Here’s how. 🧵
0:29
IlirAliu_'s profile picture

Every robot you see is a data firehose generating terabytes of chaos. This hidden crisis is the #1 reason robots fail, and it's costing the industry billions. You see hardware, but not the data swamp drowning engineers. In 2025, a quiet revolution is fixing it. Here’s how. 🧵

Ilir Aliu

1,573,730 views • 1 year ago

Do you call it 4D printing, if the platform moves as well 🤔 3D printing just got a serious upgrade A new five-axis printer can handle 70° overhangs, no support structures needed. This breaks traditional limitations and opens the door to more complex, curved designs. Perfect for engineers and designers pushing the boundaries of what’s possible. Exciting times for the future of additive manufacturing.
0:22
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Do you call it 4D printing, if the platform moves as well 🤔 3D printing just got a serious upgrade A new five-axis printer can handle 70° overhangs, no support structures needed. This breaks traditional limitations and opens the door to more complex, curved designs. Perfect for engineers and designers pushing the boundaries of what’s possible. Exciting times for the future of additive manufacturing.

Ilir Aliu

100,203 views • 1 month ago

Strawberries. Indoors. Stacked to the ceiling. Now add drones flying between the rows. In the 4D Bios setup, drones move through vertical shelves and capture high-resolution images of leaves and fruit. Instead of manual inspection, plant health becomes a data stream: > drones scan them all the time and turn ripeness, disease, and growth into real data that systems can act on. That’s when agriculture starts looking a lot like advanced manufacturing. Video: —- Weekly robotics and AI insights. Subscribe free:
1:00
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Strawberries. Indoors. Stacked to the ceiling. Now add drones flying between the rows. In the 4D Bios setup, drones move through vertical shelves and capture high-resolution images of leaves and fruit. Instead of manual inspection, plant health becomes a data stream: > drones scan them all the time and turn ripeness, disease, and growth into real data that systems can act on. That’s when agriculture starts looking a lot like advanced manufacturing. Video: —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

29,703 views • 14 days ago

Are you kidding me??? It grasps multiple objects with different ways, all at once with… a single hand??? No pauses. 1x speed. GENE-26.5 is Genesis AI’s robotics-native multimodal foundation model. It’s trained on 200,000+ hours of real human hand data (motion, force, touch) and runs on a 54-DoF bimanual system: Scaling that human data 4x lifted real-robot success rates from 16.6% to 65.6% on long-horizon dexterous tasks!! Same model weights, zero fine-tuning for this exact sequence. You know those tiny coordinated movements you do without thinking…? Robots couldn’t reliably do that before. Now they can. Today. This is the video you’ll send to my friends, outside of our bubble, when they say “robots are still just demos.” Congrats to the entire team around Zhou Xian! Credit: Seen at Zu Wang (Zu Wang) Genesis official announcement for the full story + longer demo: ——— Weekly robotics and AI insights. Subscribe free:
0:20
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Are you kidding me??? It grasps multiple objects with different ways, all at once with… a single hand??? No pauses. 1x speed. GENE-26.5 is Genesis AI’s robotics-native multimodal foundation model. It’s trained on 200,000+ hours of real human hand data (motion, force, touch) and runs on a 54-DoF bimanual system: Scaling that human data 4x lifted real-robot success rates from 16.6% to 65.6% on long-horizon dexterous tasks!! Same model weights, zero fine-tuning for this exact sequence. You know those tiny coordinated movements you do without thinking…? Robots couldn’t reliably do that before. Now they can. Today. This is the video you’ll send to my friends, outside of our bubble, when they say “robots are still just demos.” Congrats to the entire team around Zhou Xian! Credit: Seen at Zu Wang (Zu Wang) Genesis official announcement for the full story + longer demo: ——— Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

204,550 views • 3 months ago

These machines don’t look like they build the future of AI. But they do. What you are seeing is not an industrial robot just move. It is part of the process that makes the world’s most advanced chips possible. TRUMPF laser systems are used to manufacture key components for ASML’s EUV lithography machines. ❗️Without this step, modern AI hardware would simply not exist. • They machine parts with nanometer-level precision • They enable the optics and components needed for EUV lithography • Their stability directly affects chip yield and quality • No TRUMPF lasers, no ASML EUV. No EUV, no advanced AI chips. It is easy to focus on GPUs and models. But the real bottleneck sits much deeper in the industrial stack. ——- Weekly robotics and AI insights. Subscribe free:
0:29
IlirAliu_'s profile picture

These machines don’t look like they build the future of AI. But they do. What you are seeing is not an industrial robot just move. It is part of the process that makes the world’s most advanced chips possible. TRUMPF laser systems are used to manufacture key components for ASML’s EUV lithography machines. ❗️Without this step, modern AI hardware would simply not exist. • They machine parts with nanometer-level precision • They enable the optics and components needed for EUV lithography • Their stability directly affects chip yield and quality • No TRUMPF lasers, no ASML EUV. No EUV, no advanced AI chips. It is easy to focus on GPUs and models. But the real bottleneck sits much deeper in the industrial stack. ——- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

43,443 views • 24 days ago

People who’ve never set foot in a factory will never understand. I watched this three times.
0:29
IlirAliu_'s profile picture

People who’ve never set foot in a factory will never understand. I watched this three times.

Ilir Aliu

429,634 views • 10 months ago

For all my lifters: computer vision app to measure back curvature during deadlift! main technical highlights: — RF-DETR (Roboflow) to segment the person (great performance out-the-box with no additional training!) — YOLO11n (Ultralytics) for bounding box prediction around the barbell weight plate (trained on my own small dataset). — Mediapipe (Google) for pose landmark detection to guide the bounds for the line fitting. — Custom logic to fit a line across the back. about the plots on the right side: The Back Roundness Map shows the deviation of the estimated back curve from a line of best fit. Credit: Jeremy Park —— if it matters in AI or Robotics you'll see it here first:
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For all my lifters: computer vision app to measure back curvature during deadlift! main technical highlights: — RF-DETR (Roboflow) to segment the person (great performance out-the-box with no additional training!) — YOLO11n (Ultralytics) for bounding box prediction around the barbell weight plate (trained on my own small dataset). — Mediapipe (Google) for pose landmark detection to guide the bounds for the line fitting. — Custom logic to fit a line across the back. about the plots on the right side: The Back Roundness Map shows the deviation of the estimated back curve from a line of best fit. Credit: Jeremy Park —— if it matters in AI or Robotics you'll see it here first:

Ilir Aliu

234,710 views • 6 months ago

This is real time. You can see how stable the motion is. A system placing droplets between 1 nanoliter and 1 microliter inside a 96 well plate with almost perfect repeatability. No shake. No drift. No overshoot. The robot keeps the tip on track even at this scale where tiny vibrations normally ruin the result. Why this matters: •In wet lab automation, volume accuracy is everything •Nano scale tasks fail fast if the robot is even slightly off •Reliable deposition unlocks fast screening and repeatable experiments •You can run full workflows without manual checking or correction This is the kind of precision that turns lab robots from “helpful tool” into a full automation pipeline. Credit: M2-Automation GmbH —- Weekly robotics and AI insights. Subscribe free:
1:06
IlirAliu_'s profile picture

This is real time. You can see how stable the motion is. A system placing droplets between 1 nanoliter and 1 microliter inside a 96 well plate with almost perfect repeatability. No shake. No drift. No overshoot. The robot keeps the tip on track even at this scale where tiny vibrations normally ruin the result. Why this matters: •In wet lab automation, volume accuracy is everything •Nano scale tasks fail fast if the robot is even slightly off •Reliable deposition unlocks fast screening and repeatable experiments •You can run full workflows without manual checking or correction This is the kind of precision that turns lab robots from “helpful tool” into a full automation pipeline. Credit: M2-Automation GmbH —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

287,056 views • 9 months ago

40 years... just imagine! How many ideas are sitting in someone's garage right now... waiting for the technology to finally bring them to life? An old patent collected dust since 1985. William Freeman sketched a three-sided zipper. A fastener that shifts objects from flexible to rigid at the push of a button. MIT rejected his proposal. He filed the patent anyway. Last month, MIT CSAIL finally built it... The Y-Zipper. 3D-printed, three arms, only one motion. A quadruped that hardens its legs on hard surfaces, softens them on rough terrain. The zipper is the only mechanism doing that work. 40 years in a garage... one month to change how robots move. Credit: Jiaji Li | Jiaji Li 📌Article: Paper: Video: ——- If it matters in AI or Robotics, you'll read it here first:
3:58
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40 years... just imagine! How many ideas are sitting in someone's garage right now... waiting for the technology to finally bring them to life? An old patent collected dust since 1985. William Freeman sketched a three-sided zipper. A fastener that shifts objects from flexible to rigid at the push of a button. MIT rejected his proposal. He filed the patent anyway. Last month, MIT CSAIL finally built it... The Y-Zipper. 3D-printed, three arms, only one motion. A quadruped that hardens its legs on hard surfaces, softens them on rough terrain. The zipper is the only mechanism doing that work. 40 years in a garage... one month to change how robots move. Credit: Jiaji Li | Jiaji Li 📌Article: Paper: Video: ——- If it matters in AI or Robotics, you'll read it here first:

Ilir Aliu

96,328 views • 3 months ago

Everyone talks about humanoids. Meanwhile, this KUKA…
0:39
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Everyone talks about humanoids. Meanwhile, this KUKA…

Ilir Aliu

200,251 views • 8 months ago

💡 𝗩𝗘𝗥𝗦𝗔𝗧𝗜𝗟𝗜𝗧𝗬 𝗢𝗡 𝗪𝗛𝗘𝗘𝗟𝗦 𝗔𝗡𝗗 𝗟𝗘𝗚𝗦: 𝗥𝗢𝗕𝗢𝗧 𝗖𝗛𝗔𝗦𝗦𝗜𝗦 𝗕𝗥𝗘𝗔𝗞𝗧𝗛𝗥𝗢𝗨𝗚𝗛 🤖 A new era of mobility in robotics. > Hybrid design with wheels and legs > Gravity compensation for balance > Adaptable across terrains and surfaces Hybrid mobility reimagined. This robot chassis combines wheels and legs, offering flexibility and paving the way for robotics to excel in exploration and rescue missions. Gravity compensation in action. Maintaining balance across rough surfaces or uneven ground is essential in robotic mobility. Efficiency meets adaptability. Whether it's flat floors or rugged outdoor spaces, this robot is built to perform. Rescue and exploration redefined. Robots with this kind of hybrid mobility are ideal for high-risk environments like rescue operations. What applications do you see for hybrid robots?
1:03
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💡 𝗩𝗘𝗥𝗦𝗔𝗧𝗜𝗟𝗜𝗧𝗬 𝗢𝗡 𝗪𝗛𝗘𝗘𝗟𝗦 𝗔𝗡𝗗 𝗟𝗘𝗚𝗦: 𝗥𝗢𝗕𝗢𝗧 𝗖𝗛𝗔𝗦𝗦𝗜𝗦 𝗕𝗥𝗘𝗔𝗞𝗧𝗛𝗥𝗢𝗨𝗚𝗛 🤖 A new era of mobility in robotics. > Hybrid design with wheels and legs > Gravity compensation for balance > Adaptable across terrains and surfaces Hybrid mobility reimagined. This robot chassis combines wheels and legs, offering flexibility and paving the way for robotics to excel in exploration and rescue missions. Gravity compensation in action. Maintaining balance across rough surfaces or uneven ground is essential in robotic mobility. Efficiency meets adaptability. Whether it's flat floors or rugged outdoor spaces, this robot is built to perform. Rescue and exploration redefined. Robots with this kind of hybrid mobility are ideal for high-risk environments like rescue operations. What applications do you see for hybrid robots?

Ilir Aliu

33,272 views • 1 month ago

Almost no one talks about height control. This clip shows why it matters. A capacitive sensor on the cutting head keeps the nozzle only fractions of a millimeter above the metal sheet, even when the sheet is warped or vibrating. That tiny distance is everything for a clean cut. The setup here: ✅ Kimla laser system ✅ Precitec cutting head ✅ Capacitive sensing for real-time height control ✅ Stable gap over uneven or bent sheets If the nozzle drifts even slightly, you lose cut quality, speed, and consistency. This is the part of laser systems that most people never think about, but it is what makes the difference between “it works” and “this is production ready.” Have you ever had to keep the nozzle as close as possible without risking a crash? Credit: Daltons Wadkin —- Weekly robotics and AI insights. Subscribe free:
0:20
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Almost no one talks about height control. This clip shows why it matters. A capacitive sensor on the cutting head keeps the nozzle only fractions of a millimeter above the metal sheet, even when the sheet is warped or vibrating. That tiny distance is everything for a clean cut. The setup here: ✅ Kimla laser system ✅ Precitec cutting head ✅ Capacitive sensing for real-time height control ✅ Stable gap over uneven or bent sheets If the nozzle drifts even slightly, you lose cut quality, speed, and consistency. This is the part of laser systems that most people never think about, but it is what makes the difference between “it works” and “this is production ready.” Have you ever had to keep the nozzle as close as possible without risking a crash? Credit: Daltons Wadkin —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

224,579 views • 9 months ago

Triple inverted pendulum in transition control A classic control problem, done in real time. This setup moves smoothly between all eight equilibrium points of a triple inverted pendulum. The system reacts every 1 millisecond, which shows how fast modern control loops can be. • Real-time control at 1 ms sampling • Stable transitions between multiple balance points • Built with Simulink and LW-RCP02 hardware This is a beautiful example of how theory meets practice in advanced control engineering. Video: Credit: Embedded Control Lab, Inha University —- Weekly robotics and AI insights. Subscribe free:
1:09
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Triple inverted pendulum in transition control A classic control problem, done in real time. This setup moves smoothly between all eight equilibrium points of a triple inverted pendulum. The system reacts every 1 millisecond, which shows how fast modern control loops can be. • Real-time control at 1 ms sampling • Stable transitions between multiple balance points • Built with Simulink and LW-RCP02 hardware This is a beautiful example of how theory meets practice in advanced control engineering. Video: Credit: Embedded Control Lab, Inha University —- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

168,127 views • 7 months ago

Now all you need to make tactile sensors is a 3D printer, magnets, and magnetometers! [📍It’s open source!] A new tactile sensor, called e-Flesh, with a simple working principle… measure deformations in 3D printable microstructures. Since e-Flesh is 3D printable, you can make it in all shapes and sizes for applications ranging from foot fall sensing to multifingered hands. This is critical in getting touch not just on fingertips, but all around robots. eFlesh can democratize touch sensing with open-sourced❗️ Make your own: Paper:
0:57
IlirAliu_'s profile picture

Now all you need to make tactile sensors is a 3D printer, magnets, and magnetometers! [📍It’s open source!] A new tactile sensor, called e-Flesh, with a simple working principle… measure deformations in 3D printable microstructures. Since e-Flesh is 3D printable, you can make it in all shapes and sizes for applications ranging from foot fall sensing to multifingered hands. This is critical in getting touch not just on fingertips, but all around robots. eFlesh can democratize touch sensing with open-sourced❗️ Make your own: Paper:

Ilir Aliu

154,953 views • 7 months ago