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Picking up trash requires a lot of dexterity and will come with many challenges, but I think it’s a simpler problem than many household tasks and it’s probably on par for what these tests show is doable.
I think you’re going to have to PR challenges getting people to welcome robots into their homes. If you have robots out in cities providing a public good, not only do they serve as walking advertisements for your company, you’re going to earn some trust before you’re ready deploy them into private spaces.
Plus, governments (or perhaps HOAs for wealthy communities) can be good early customers since you can have a focused sales strategy. Politicians love these types of visible quality of life improvement projects. If you can show that your robots, working round the clock, can decrease litter at a low cost, many cities are going to want to buy them.
The idea sounds good, but I'm curious about the "low cost" part. How do you account for vandalism and theft? A sidewalk robot seems like an easy target for being damaged, stripped for parts, or simply stolen.
You could just buy cartons of cigarettes and chop off the butts, at that rate.
I joke, but this is surely what would eventuate.
I doubt wealthy HOA communities have much random trash to pick up in the first place
And it’s fast, they do lots of resets. I feel like they are spending too much money but I’m not complaining. Best 200$ for an AI subscription IMHO
Our developers and their agents will never long for a road map the next time they need to build something that touches code across multiple repositories. This is the kind of documentation product that nobody ever had time to build in the olden days. And now, we can get it on a Saturday in about 20 minutes.
What's coming in six months?
I think the specific innovation here is that it figured out interesting ways to get itself to the goal. Which I think is likely what's going on here with the robot arms stuff too. They've figured out some sauce to uncork better "planning" and problem solving to get to some stated end.
Of course these are also the kinds of things that can make a model figure out how to break out of a security sandbox, too.
Not to say it was perfect, e.g. sometimes it would get temporarily stuck in a testing loop or it would test scenarios that didn't necessarily seem reasonable. But overall rather effective and capable. This was for a city building game so pre-scripted builds, even if by AI, are likely much easier to create and execute than say playing an ARPG.
We can build robots that do the things you want. Arrange a visit to Amazon's robot warehouse tour.
We can't ship them because they break all the time with current technology. It would be a tough sell to have to being in a 100kg robot for servicing every few weeks.
This was cars in the first several decades of automobiles. The tide shifted as soon as you could just drive the car to a neighborhood dealership for servicing. It's fun to imagine the logistics of that for robots but the material science and engineering has to advance a bit.
Only sort of kidding, tbh having bots service themselves (and being intentionally made in a way that they can service each other) just makes a lot of sense.
It almost feels like "A robot shall not autonomously build or repair another robot" should have been another of Asimov's laws.
We're not there yet, but I think we're a lot closer than most people realize.
I am trying to understand in your view what are the parts that actually breaks and what kind of improvement we would need.
Passing on what I have heard from robotics researchers at lunch conversations.
My impression is that any moving part that is not an electric motor or an hinge breaks.
Human arms and hands are incredibly intricate. Reproducing their facility with hardware requires a large number of actuators and finicky fine parts. This isn't a software problem. Industry solves it with maintenance schedules.
There's probably nothing in your house that has as many moving parts as a robot needs. Your car maybe, and pretty much all it does is rotate wheels.
But you can't buy it because it'll break in about seven days.
I'm not holding my breath for advanced robots in the home within the next ten years.
But, then again, I didn't see LLMs coming either.
Seeing them play Portal and other video games, I'm curious if they will eventually help solve that last N% of self-driving.
[1] https://waymo.com/blog/2025/12/demonstrably-safe-ai-for-auto...
Imagine if someone finds a weird image pattern that gets misinterpreted as instructions and hangs that off a bridge over a freeway.
I'm skeptical, tho. Cost will push for right sizing, much like we have right sized a lot of things about modern cars.
ASTRA HAS BEEN UTTER SHIT.
It is much more expensive than Sol 5.6 Medium / High and did nothing but write unit tests and junk code, despite having access to the vendor original source, an API, and the full tank specs.
Failure Examples:
* In two instances had the direction of the servos wrong.
* Calculated the maximum extent of the gripper wrong, and the closure, so it didn't grip.
* Code failed to take into account the gripper requires continuous torque when lifting a pair of socks, so couldn't lift.
* Failed to actually start physical testing more than opening and closing the gripper, and that was when I asked about progress.
* Code failed quite spectacularly to calculate camera gimbal extent range correctly.
* Code failed to use the ultrasonic in range to target until I pointed it out, the skill also didn't advise gimbal angle adjustment to correct range overshoot to the wall behind a small object.
The test environment has both an onboard ultrasonic for distance, onboard camera, and a bird eyes view camera (birds eyes only while training).
I've stopped using Astra Low (default) and gone back to Sol 5.6 low/medium/high for the training, it's cheaper and now I'm back to fine tuning, after it had to redo large chunk of the gripper/arm code and prevent unnecessary hard stop code kicking in based on the wrong profiling.
It's cost me around 1000 to 1250 credits (£50), burnt in around 2 hours, looking mostly at recorded video, and photos, and writing bad code based on bad assumptions. I've also burnt through regular Plus 5 hour quota in about 30-45 minutes with it.
Really weird model. No idea how it did so well on all the benchmarks.
good fucking job everyone, congrats.