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Helix: A vision-language-action model for generalist humanoid control

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141–150 of 178 posts

Re: Helix: A vision-language-action model for generalist humanoid control

#141
post #75

Earlier quoted context omitted.

The thing in the video moves slower than the sloth in Zootopia. If you die by that robot, you probably deserve it.

From a different robot (Boston Dynamics' new Atlas) - the system moves at a "reasonable" speed. But watch at 1m20s in this video[1]. You can see it bump and then move VERY quickly -- with speed that would certainly damage something, or hurt someone. [1] https://www.youtube.com/watch?v=F_7IPm7f1vI

Especially if holding a knife or something sharp.

Re: Helix: A vision-language-action model for generalist humanoid control

#142

Earlier quoted context omitted.

We had sufficient AI to make death machines for decades. You don't need fancy LLMs to get a pretty good success rate for targeting. I have said for years that the only thing keeping us from "stabby the robot" is solving the power problem. If you can keep a drone going for a week, you have a killing machine. Use blades to avoid running out of ammo. Use IR detection to find the jugular. Stab, stab and move on. I'm gues…

> We had sufficient AI to make death machines for decades And we already reached the peek here. Small drones that are cheaply mass produced, fly on SIM cards alone and explode when they reached a target. That's all there is to it. You don't need a gun mounted on a spot or a humanoid robot carrying a gun. Exploding swarms are enough.

Black Mirror has the perfect episode for this scenario already.

Re: Helix: A vision-language-action model for generalist humanoid control

#143

Why do they make “eye contact” after every hand off? Feels oddly forced.

If you're training robots to interact with humans this is the kind of behavior you'd want. Humans use a ton of nonverbal hints like this to register context.

Re: Helix: A vision-language-action model for generalist humanoid control

#144
post #11

Earlier quoted context omitted.

It probably gives them confidence that they can accurately see a thing even though they don't know what that thing is. I could also imagine a lot of safety around leaving things outside of the current task alone so you might have to bend over backwards to get new objects worked on.

There is no such thing as "thing" here. These models are trained such that the given conditions (the visual input and the text prompt) will be continued with a desirable continuation (motor function over time). The only dimension accuracy can apply to is desirability.

You don't think there's any segmentation going on?

Re: Helix: A vision-language-action model for generalist humanoid control

#146
post #116

The demo is quite interesting but I am mostly intrigued by the claim that it is running totally local to each robot. It seems to use some agentic decision making but the article doesn't touch on that. What possible combo of model types are they stringing together? Or is this something novel? The article mentions that the system in each robot uses two ai models. S2 is built on a 7B-parameter open-source, open-weight V…

It looks pretty obvious (I think):

1. S2 is a 7B VLM, it is responsible for taken in camera streams (from however many of them), run through prompt guided text generation, and before the lm_head (or a few layers leading to it), directly take the latent encoding;

2. S1 is where they collected a few hundreds hours of teleoperating data, retrospectively come up with prompt for 1, then train from the scratch;

Whether S2 finetuned with S1 or not is an open question, at least there is a MLP adapter that is finetuned, but could be the whole 7B VLM is finetuned too.

It looks plausible, but I am still skeptical about the generalization claim given it is all fine-tuned with household tasks. But nowadays, it is really difficult to understand how these models generalize.

Re: Helix: A vision-language-action model for generalist humanoid control

#147
post #46

I don't know, there has been so many overhyped and faked demos in humanoid robotics space over the last couple years, it is difficult to believe what is clearly a demo release for shareholders. Would love to see some demonstration in a less controlled environment.

I suppose the next big milestone is Wozniak's Coffee Test: A robot is to enter a random home and figure out how to make coffee with whatever they have.

That could still be decades away.

Re: Helix: A vision-language-action model for generalist humanoid control

#148
post #67

I'm always wondering at the safety measures on these things. How much force is in those motors? This is basically safety-critical stuff but with LLMs. Hallucinating wrong answers in text is bad, hallucinating that your chest is a drawer to pull open is very bad.

You can have dedicated controllers for the motors that limit their max torque.

Re: Helix: A vision-language-action model for generalist humanoid control

#149
post #80
post #75

Earlier quoted context omitted.

The thing in the video moves slower than the sloth in Zootopia. If you die by that robot, you probably deserve it.

Are you saying it cannot move faster than they because of some kind of governor?

That is how I would design it. It is common in safety critical PLC systems to have 1 or more separate safety PLCs that try to prevent bad things from happening.

Re: Helix: A vision-language-action model for generalist humanoid control

#150

Earlier quoted context omitted.

> We had sufficient AI to make death machines for decades And we already reached the peek here. Small drones that are cheaply mass produced, fly on SIM cards alone and explode when they reached a target. That's all there is to it. You don't need a gun mounted on a spot or a humanoid robot carrying a gun. Exploding swarms are enough.

Black Mirror has the perfect episode for this scenario already.

Except those things would be very easily defeated by a 12 gauge shotgun or a AR-15
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