Latest Robots that can replace workers

[testerjp]

Can collaborate between robots and can learn a lot faster, takes command through voice and don't require much training.

Slow like fug but they can work 24 hours, meaning 3 times more than humans on an average work day with no off day, no leave, no bonus, no kpkb.

Those who keeps thinking AI is a hype and useless, i hope it's a reality check to you.
This is only one of the big disruptions it can bring.

This is the update:

Introducing Helix​

We're introducing Helix, a generalist Vision-Language-Action (VLA) model that unifies perception, language understanding, and learned control to overcome multiple longstanding challenges in robotics. Helix is a series of firsts:

• Full-upper-body control: Helix is the first VLA to output high-rate continuous control of the entire humanoid upper body, including wrists, torso, head, and individual fingers.
• Multi-robot collaboration: Helix is the first VLA to operate simultaneously on two robots, enabling them to solve a shared, long-horizon manipulation task with items they have never seen before.
• Pick up anything: Figure robots equipped with Helix can now pick up virtually any small household object, including thousands of items they have never encountered before, simply by following natural language prompts.
• One neural network: Unlike prior approaches, Helix uses a single set of neural network weights to learn all behaviors—picking and placing items, using drawers and refrigerators, and cross-robot interaction—without any task-specific fine-tuning.
• Commercial-ready: Helix is the first VLA that runs entirely onboard embedded low-power-consumption GPUs, making it immediately ready for commercial deployment.

New Scaling for Humanoid Robotics

The home presents robotics' greatest challenge. Unlike controlled industrial settings, homes are filled with countless objects–delicate glassware, crumpled clothing, scattered toys–each with unpredictable shapes, sizes, colors, and textures. For robots to be useful in households, they will need to be capable of generating intelligent new behaviors on-demand, especially for objects they've never seen before.

The current state of robotics will not scale to the home without a step change. Teaching robots even a single new behavior currently requires substantial human effort: either hours of PhD-level expert manual programming or thousands of demonstrations. Both are prohibitively expensive when we consider how vast the problem of the home truly is.

Figure 1: Scaling curves for different approaches to acquiring new robot skills. In conventional heuristic manipulation, skills grow with PhDs who manually script them. In conventional robot imitation learning, skills scale with data collected. With Helix, new skills can be specified on the fly with language.
But other domains of AI have mastered this kind of instant generalization. What if we could simply translate the rich semantic knowledge captured in Vision Language Models (VLMs) directly into robot actions? This new capability would fundamentally alter robotics' scaling trajectory (Figure 1). Suddenly, new skills that once took hundreds of demonstrations could be obtained instantly just by talking to robots in natural language. The key problem becomes: how do we extract all this common-sense knowledge from VLMs and translate it into generalizable robot control? We built Helix to bridge this gap


This was 3 months ago when they were deployed at BMW.
Now that the robots can integrate to work together, it means can perform more automation




Meanwhile, China's Robots only seem to focus on maneuverability and do stupid things like dancing

 

[dambio]

Slow at 1st later can upgrade n tune 1.

 

[Hello_Kitty]

look like C3PO

 

[khratit]

If can replace already fighting land wars with drones

Kana set on fire I will laugh my sinkhole off

Cheapest way to destroy electronics, set them on fire

 

[tootired]

Can collaborate between robots and can learn a lot faster.
Slow like fug but they can work 24 hours, meaning 3 times more than humans on an average work day with no off day, no leave, no bonus, no kpkb.
This is the update:
Introducing Helix
We're introducing Helix, a generalist Vision-Language-Action (VLA) model that unifies perception, language understanding, and learned control to overcome multiple longstanding challenges in robotics. Helix is a series of firsts:
Full-upper-body control
: Helix is the first VLA to output high-rate continuous control of the entire humanoid upper body, including wrists, torso, head, and individual fingers.
Multi-robot collaboration
: Helix is the first VLA to operate simultaneously on two robots, enabling them to solve a shared, long-horizon manipulation task with items they have never seen before.
Pick up anything:
Figure robots equipped with Helix can now pick up virtually any small household object, including thousands of items they have never encountered before, simply by following natural language prompts.
One neural network
: Unlike prior approaches, Helix uses a single set of neural network weights to learn all behaviors—picking and placing items, using drawers and refrigerators, and cross-robot interaction—without any task-specific fine-tuning.
Commercial-ready
: Helix is the first VLA that runs entirely onboard embedded low-power-consumption GPUs, making it immediately ready for commercial deployment.
New Scaling for Humanoid Robotics
The home presents robotics' greatest challenge. Unlike controlled industrial settings, homes are filled with countless objects–delicate glassware, crumpled clothing, scattered toys–each with unpredictable shapes, sizes, colors, and textures. For robots to be useful in households, they will need to be capable of generating intelligent new behaviors on-demand, especially for objects they've never seen before.
The current state of robotics will not scale to the home without a step change. Teaching robots even a single new behavior currently requires substantial human effort: either hours of PhD-level expert manual programming or thousands of demonstrations. Both are prohibitively expensive when we consider how vast the problem of the home truly is.

Figure 1: Scaling curves for different approaches to acquiring new robot skills. In conventional heuristic manipulation, skills grow with PhDs who manually script them. In conventional robot imitation learning, skills scale with data collected. With Helix, new skills can be specified on the fly with language.
But other domains of AI have mastered this kind of instant generalization. What if we could simply translate the rich semantic knowledge captured in Vision Language Models (VLMs) directly into robot actions? This new capability would fundamentally alter robotics' scaling trajectory (Figure 1). Suddenly, new skills that once took hundreds of demonstrations could be obtained instantly just by talking to robots in natural language. The key problem becomes: how do we extract all this common-sense knowledge from VLMs and translate it into generalizable robot control? We built Helix to bridge this gap
This was 3 months ago when they were deployed at BMW.
Now that the robots can integrate to work together, it means can perform more automation

Meanwhile, China's Robots only seem to focus on maneuverability and do stupid things like dancing

learning or new task are slow but routine, they can speed up and more precise and consistent.


Read HWZ Forum Rules!

 

[ghregular]

gd luck to humanrace who created smthg to annihilate themselves

 

[testerjp]

learning or new task are slow but routine, they can speed up and more precise and consistent.


Read HWZ Forum Rules!

Not only that.

Cost of robots I remember decrease by about 20 pct a year which means an improving ROI. So eventually mass adoption will be widespread.

This will be bad news for manufacturing hubs.

 

[artncraft]

Amazing that they can collaborate.

This is a very advanced form of AI.

 

[tootired]

Not only that.
Cost of robots I remember decrease by about 20 pct a year which means an improving on the ROI. So eventually mass adoption will be widespread.
This will be bad news for manufacturing hubs.

made in china humanoid definitely cheap enough for everyone. will buy one as helper in home.


Read HWZ Forum Rules!

 

[nasfieldjohn]

How much per robot
Definitely not cheap if got advance ai
Factory cheaper at 3rd world countries

 

[Apparatus]

Can help sinkie employers solve their labor shortage especially in the F&B and eatery sectors

 

[testerjp]

How much per robot
Definitely not cheap if got advance ai
Factory cheaper at 3rd world countries

Robot's price is always dropping, the robot factories can even mass produce using their own robots.
For industrial usage, you need reliability and the robots will pay for themselves.

It's not the hardware, it's the software and upgradability.

Here's an article from 2019. I remember there's a newer article
https://www.ark-invest.com/articles/analyst-research/industrial-robot-cost-declines

 

[testerjp]

Can help sinkie employers solve their labor shortage especially in the F&B and eatery sectors

Of course can.

This is using at best GPT 4 o1 kind of AI.
GPT 5 is coming which should see better efficacies and more capabilities.

For specific roles, they can design the robots to be different, like for dishwashing, cleaning tables, etc.
To be water resistant, to be shock resistance or EMP shielded for military, etc
They don't necessarily need to look humanoid.

 

[buttbERry]

in before skynet

 

[PaboJames]

Maybe America labour unions going to strike soon... If these robots replace their jobs

 

[Bumperbee88]

 

[mocax]

skali one day they dulan the boss, and plan with other robots to whack him...

 

[FireEmblem]

Most current jobs will be gone within the next 10 years.

 

[Travis_Touchdown]

all these developments too wols riaoz... can faster??

 

[Racking2322]

The slowness is a problem. Even can work long, fact is ppl need the task delivered fast.

Anyway can try these robots at McDonald's and see how.