i2RT
@i2rt_robotics
Robotic hardware that you can actually deploy in real world. Email [email protected] for inquiries!
Mama I’m on TV 🥹
Excited to announce that we have raised $120M in our Series A to advance the frontier of general-purpose high-performance robots. 🤖 The new funding will accelerate progress towards our mission of bringing foundation-model powered robots to everyone, everywhere. Read more 👇
Excited to share our latest progress on DYNA-1 pre-training! 🤖 The base model now can perform diverse, dexterous tasks (laundry folding, package sorting, …) without any post-training, even in unseen environments. This powerful base also allows extremely efficient fine-tuning…
It's 2025. If you work in hospitality and think it should be automated — it should. Meet Nemo3 by @VerneRobotics: a dexterous, general-purpose hospitality robot. Laundry. Towel folding. Amenity kits. We do the jobs other robots find too hard. Book a demo →…
Growing my skill sets on a daily basis 🐣
Excited to share our latest progress on DYNA-1 pre-training! 🤖 The base model now can perform diverse, dexterous tasks (laundry folding, package sorting, …) without any post-training, even in unseen environments. This powerful base also allows extremely efficient fine-tuning…
I could have helped but you chose to let me sit there and watch 🧐
On-policy probing from a strong base model + off-policy residual learning + distillation might be a right formula for VLA post-training. The most interesting part to me is the intriguing cross-task generalization after distillation. Check out the PLD project led by @_wenlixiao…
What if robots could improve themselves by learning from their own failures in the real-world? Introducing 𝗣𝗟𝗗 (𝗣𝗿𝗼𝗯𝗲, 𝗟𝗲𝗮𝗿𝗻, 𝗗𝗶𝘀𝘁𝗶𝗹𝗹) — a recipe that enables Vision-Language-Action (VLA) models to self-improve for high-precision manipulation tasks. PLD…
it’s just matter of time before we see YAMs start assembling YAMs 🥹
What if robots could improve themselves by learning from their own failures in the real-world? Introducing 𝗣𝗟𝗗 (𝗣𝗿𝗼𝗯𝗲, 𝗟𝗲𝗮𝗿𝗻, 𝗗𝗶𝘀𝘁𝗶𝗹𝗹) — a recipe that enables Vision-Language-Action (VLA) models to self-improve for high-precision manipulation tasks. PLD…
Behind the scene: how are YAMs made? You’re watching the manufacturing process of J2 actuator on YAM Pro and YAM Ultra.
Who wants to see what’s inside a YAM that makes it so delicious? when i say vertical integration i mean we make the motor that make the YAM arm and therefore we’re able to achieve the best-in-class system-level performance. Follow and I’ll share more on what’s inside the YAM…
Thanks @DJiafei !! One of the missions here at i2RT is to democratize capable hardware for physical intelligence 🚀
This is why I’m bullish that the coming years will mark a turning point for robotics: as capable hardware becomes more accessible and affordable, large-scale adoption and real-world impact will finally be within reach. Great arms from @i2rt_robotics !
Dancing in the moonlight 👯♂️ YAM EOL testing. All YAM customers, send me your vin number etched at bottom and I’ll share your arm’s little cute dance video.
Each increment here is 2 µm, 1/35 of the thickness of your hair Repeatability matters. Even for low cost arms. (Please watch because someone spent 1 hour setting this up today)
That’s why we grind our own gears, wind our own motor and fabricate controller board all in-house.
True system-level performance comes from controlling every layer, not just assembling off-the-shelf parts.
This is what fundamentally makes i2RT different - vertical integration from open-source code down to the motor/gearbox/ controller manufacturing. There are no shortcuts to system-level high performance.
Hold my beer 🤡
This dude shows you how to fold a t shirt in 3 seconds
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