Anyone reading this who works/runs a robotics company, I really want to encourage you to build a robot to pick up trash on city sidewalks as an early product.

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.

If you haven’t tried computer use with Astra with codex I highly highly recommend it. Just like how gpt 4 and agentic coding with cc. This thing is the most exciting stuff I’ve seen in a while. And then all the blender, cad stuff is cherry on top.

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

LLM's are a funny technology because on the one hand this is all undeniably impressive at the rate of what's changed from them, and yet despite that I find myself disappointed by the lack of breakthroughs for things I don't find interesting. I like math and programming, and LLM's are pretty good at it, when are they going to get good at folding laundry for me? I think a lot of robotics work promises to solve this category of "boring" breakthroughs, and I'm optimistic we'll be able to achieve it, i just wonder when

I think we need to be honest here. Author is basing it on one small experiment of picking up a block, relies on an whole IK controller pipeline to do the job, and does not compare it to full VLA or WAM models. They then proceeded to extrapolate the token throughput (mind you not the same as controller throughput) into supposed 2029 timeline, from one example.

Code as policy is a bad interface in my opinion, but VLM planning has promise. This has been tried in 2022 https://say-can.github.io/, and recently reformulated in https://lianegalanti.github.io/Pigey/

Thing is even recent Gemini Robotics 2 argues for architecture that has a VLM planner and then a VLA/WAM controller + a local small VLA model when connection disappears. And recent SOTA architectures rely on hierarchical design. I think this might be a sensible way to go about it. If you were to train GPT-X on robotics data and to output actions, congratulations! you've just made a VLA. It is enticing for people to just wish for one architecture to do it all, which is why we get stuff like this. I think there is a lot more to gain from modularity and we should not be afraid of specialization.

I’m honestly blown away by Astra, I told it to build me a fairly complex game I’ve been procrastinating on for more than a year and left it running overnight with computer use and full access enabled. Next morning I had a fully functional game built. It downloaded Unity, Blender and GIMP and built all the assets as well as the complete game without me having to do anything, the game is not trivial at all and nor are the assets.

I don't know much about robotics engineering, so I just wanted to give kudos to the Robocurve team on this write-up.

Even for an absolute robotics newbie such as myself, the article was interesting to read, and easy to understand. Plus it was straight to the point, with no unnecessary waffle.

Just a pleasure all round. Well done Robocurve.

Are LLMs going to eventually become the architecture that powers self-driving cars?

Seeing them play Portal and other video games, I'm curious if they will eventually help solve that last N% of self-driving.

The costs will need to go way way down either through chips (but then less updating) or something else. $2 to put away a block is very expensive labor.

how is anyone going to afford robots if no one can work

The limitations that they state shouldn't really make much of a impact. But it was nice of them (and not to mention, real unbiased research) to mention those. Kudos to them!

For the last 2 days I've been trying to create a skill for Openclaw that would allow traditional control of the Adeept Tank's robot arm (a small open source toy tank that looks like a bomb disposal robot).

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.

so we finally got our "phd level ai" maybe, semi consistently move blocks around at the level of a 1 year old child.

good fucking job everyone, congrats.

Stupid!! GPT models are not for that. You need specific one for robotic.