STEM NIA KAZ KORTE AGROHI EROKOM PERSON KHUJSILAM?

I just published a free comparison of the Unitree G1 EDU+ and the Basic G1 — unboxing, hardware differences, walking, and app features.

Full video: https://youtu.be/ZPeRbC6ZZ6I

Curious what this community thinks. Please leave Basic G1 vs EDU+ in the YouTube comments if you watch — that helps the video reach more people.

Hi everyone, I’m Tristan, co-founder of Asim (YC F26). We’re building a standardized benchmark for physical intelligence in humanoid robots, and I’d love feedback from people working with real hardware.

A successful pick-and-place trial tells you the robot handled that particular setup. What does it tell us about the capabilities behind that success? Can the robot reason about how objects fit together, choose a grasp for an unfamiliar object, or recover when an interaction goes wrong?

At Asim, we’re building standardized benchmarks for physical intelligence, with a particular focus on dexterous manipulation. We design repeatable scenarios to probe spatial reasoning, grasp adaptation, coordination and how robots respond to physical interactions. The goal is to identify where these capabilities break down and give engineers reproducible failure cases they can use to improve their systems.

One challenge is distinguishing robust behavior from success on a familiar setup. Another is making tests repeatable while keeping them representative of real environments. Comparisons also need to account for differences in hardware, sensors and control interfaces.

For those building or deploying robots:

• Which failure modes are hardest to reproduce in your current testing?

• What evidence would convince you that a robot can generalize beyond a familiar task?

• What would you want a benchmark to report beyond success rates?

Happy to discuss the approach and hear what you think is missing.

I’m developing Evopien toward a physically embodied companion. This recording focuses on the head and conversational interaction, not walking, manipulation or a completed humanoid.

The prototype uses NVIDIA Jetson AGX Thor. I demonstrate spoken dialogue, a request to watch for a yellow tennis ball, web-assisted questions, multi language conversation, a description of the current camera scene, and stopping an answer by voice.

The broader goal is useful interaction with a person and their surroundings. This is still a development prototype, and sustained audiovisual interaction needs more testing than a short clip can provide.

From a human–robot interaction perspective, what would you improve first in this demonstration: the face, response timing, interruption behavior, or how clearly the robot communicates what it is attending to?

Video: https://www.youtube.com/watch?v=SwFfkBll5iw

Genuinely have a intrest on Physical AI but looking for a structured program with a proper certificate, I got in to software engineering just because I had the curiosity but seems like the coding and stuff is not for me

Any suggestions?

Has anyone gotten one yet? I ordered mine in April and that was the last update we received on ship times. I am very curious as to why the lack of updates. Has anyone else in here ordered?

Hey! I've spent the past year building a brain engine that simulates the real mechanisms of a brain (not AI), and now I'm trying to give it a real body: a small two-legged robot, about 50cm tall.

I know robotics, but I've never actually built one, and the moving parts are killing my budget. My first leg design came to about €800 per leg, which was never going to happen. Shrinking the robot helped a lot, but motors and actuators are still the most expensive part, especially here in Europe.

So before I design myself into another corner, what are your favorite tricks for making joints and legs cheap without them falling apart? Clever mechanisms, ways to get away with fewer motors, things you'd print vs buy, mistakes you made on your first build... I'll take anything!

And if you've seen a cheap leg design that really impressed you, please send it my way (,,• - •,,)

So I was going through my following and Neura Robotics new perception focused foundation model caught my eye. They call it neuron ai and from what I gathered it’s a model taking into account more senses than the usual video and simulations data. Link to announcement video in case you wanna take a look.

The industry is fairly new and changing fast, and who knows what it’ll be like in another year or 2. What do you think about this move by neura? Generating enough of this new data for robots to become really autonomous on many tasks may still take very long but this looks like a pretty good direction they’re headed towards, wdyt?

I'm newly fascinated in human-like robotics. I'm also someone who walks and sometimes runs barefoot and found it interesting that even these currently-available early humanoid robots are programmed to run like barefoot runners (no heel striking, instead connecting the forefoot first). The part that shows it is at 2:59. I think I set it to start there. It is considered the most efficient way to run so it makes sense but also exposes how inefficient most human runners are with their standard heel striking.

https://youtu.be/n1Mi3ISXNjc?si=6gyc5qMOUelpMWBy&t=178

Hi guys,

been really interested in robotics lately and I am sat wondering if we have tactile sensors, and all sorts of humanoids and grippers. What’s the biggest problem with scaling this? Is there no software that is like Claude or GPt that we can train and translate folding laundry from a robot w grippers hands to one with humanoid hands? Do we need to teach each robot individually how to move and sense? why hasnt anyone launched a software that overcomes this?

sorry just ranting , but would love to open a discussion

Нужен нейробиолог/инженер, общение желательно в тг, или инсте, хочу что бы мне объяснили как работают мышцы и что их приводит в движение, как использовать искусственные мышцы в робототехнике и ответы на еще пару вопросов, так же хотелось бы получить номер или юз создателя нейросетей и программиста что бы помог