Hacker News new | ask | show | jobs
by adityashankar 2 days ago
I work in this field, and I wrote my bachelor's thesis here, not with humanoids but with VLAs (think chatgpt connected to a robot arm)

It's certainly not there yet for anything practical, there's also certain bits and structures that don't have accurate names during construction, and it is important to keep that in mind - so a robot is unlikely to understand what it means to say "put the left bit of this box onto this right bit" due to ambiguity, a human would understand that

Plus we have no good reliable accuracy testing data in most cases (most tests occur on a few demos, but that isn't a good representation of how must things work), popular benchmarks, such as libero have been saturated, and nearly everything gets 95% there, most companies and researchers have their own benchmarks here.

Plus companies lie alot, and do very dangerous things in thier videos, I.e. these robots should not be standing very close to humans, because of being dangerous.

There are also legitimate concerns of misuse of these robots that need to be accounted for, misuse does not have to be warfare, but can be as simple as confusing it while it is cutting tomatoes with a knife.

Turning doorknob is easy, and fail recovery is also being worked on, but we don't have reliable statistics anywhere on that. The hard part is on practical things, as in when placing bricks or attaching a part during manufacturing it needs to ensure that it is aligning everything correctly....and that's hard, while it is impressive, it is very irresponsible to keep humanoids at home (people are irresponsible when untrained), for example, lawnmowers injure about 6400 people a year...and that is not an everything machine.

Humanoids in general are...not appealing in specific, due to maintainable of joints, complexity, but robot arms in particular, expecially on wheels (check mobile aloha), are likely to be able to do tasks such as clean up in hotels, after a guest had left, or replace some cooks in restaurants (if their work is consistent)

1 comments

This is absolutely not true check out Sunday robotics and their robot that folds clothes. Sunday robotics says it does holding of clothes correctly 99% of the time that is real world usage today. They even have three hour video of the robot folding the clothes.
They didn't mention anything about folding clothes so I suspect this comment is just an ad
It’s a video on their YouTube channel
No, the above is absolutely exactly true. Robots folding clothes and tying shoelaces etc is nothing but a tech demo at this point.

It's difficult to grok this because if you watch a human folding a t-shirt, you can reliably predict that the same human will fold a different t-shirt just as well, and in fact be perfectly capable of folding a wide variety of other clothes items as well. Not so for robots. With robots, what you see is precisely what you get. If you see a robot folding a t-shirt, all that means is that that particular robot can fold that particular t-shirt. The state of the art today is that the same robot cannot be expected to be able to fold a different t-shirt.

For example, see this article about Mobile ALOHA at Google. There's a passage where the visiting, awe-struck, journalist asks whether the robot he's just seen tying up a pair of shoelaces can tie up his own shoe.

“If I gave it my shoe,” I ventured, “would it just totally fail?”

“We could try,” Tompson said. I removed my right sneaker, with apologies to anyone forced to handle it. Tompson gamely placed it on the table, while Driess reloaded the policy.

“To set expectations,” Driess said, “this is a task that is thought of as being impossible.”

Tompson eyed his new experimental subject with some trepidation. “Very short shoelaces,” he said.

The policy booted up, and the claws set to work. This time, they poked at the shoelace without getting a grip. “Do you give consent for your shoe to be destroyed?” Driess joked, as the hands grabbed at the tongue. Tompson let them try for a few more seconds before hitting the Failure pedal.

https://archive.ph/CiJJG#selection-1887.0-1915.291

(Original: https://www.newyorker.com/magazine/2024/12/02/a-revolution-i...)

As to ACT-2 which basically uses the same techniques as ALOHA (imitation learning) far as I can tell, that's a commercial product and the information they give on their site is difficult to parse. E.g. they say they have 99.1% ±0.3 success rate, 778 successful folds and 9 garment types which is low enough to engender some trust they're not trying to inflate their numbers, but they don't say whether they trained on the garments used in evaluation or not. Chances are they did, because that's the current limit of the technology, i.e. if the garment being folded is unseen (as opposed to the environment, which they tout) then performance is basically random. So either ACT-2 have a major breakthrough that is a few leaps and bounds away from the current state of the art, or you've just watched a tech demo.

The fact that they only advertise "9 garment types" though is a big hint: they have the same problem with generalisation as everybody else at this point in time.

You make some very good points about the ACT-2 if it’s nine garment types that’s still very acceptable but the point you bought up about them training on exactly those pieces of garments is a possibility.