xanderjanz

@Jinyibruceli

Hi thanks for the question! HN flagged your comment, so I'll respond here.

You said: "I tried building a hexapod last year and the hardest part wasn't the printing, it was figuring out which servo library worked with which controller board. The Github repos were all over the place with dependencies. Does orobot normalize the BOM and software stack info, or is it mainly aggregating the STLs? I'm curious if the agent-generated content catches stuff like "this uses a deprecated ROS package" or incompatible firmware versions."

1) Yep it normalizes BOMs, whether it's on personal blogs, google docs, github, markdown, html, wherever. Agreed they are all over the place and hard to navigate, but LLM agents are really good at this. As much as it can, it tries to build a single one-click Amazon add to cart with everything in it. If parts aren't on Amazon, it prefers Alibaba next, or they're linked separately. Because some projects online are forks and only have BOM lists for their additions, so you need parts from the fork and the original BOM list, orobot puts both in one spot.

2) Yes orobot writes on-device javascript commands to git pull and run Makefiles or do whatever else it has to do to bootstrap. And that's installed over wifi through the app.

3) Yes the Agent install code definitely should fixup deprecated ROS libraries. Either internally to orobot.io, and it even will post push requests upstream, if there are bugs buried in the source GitHub project. Weather or not it has I'm not sure. Some of this is really new.

I don't want to promise anything I haven't tried myself. Can you link which hexapod github projects you were trying and if they're on orobotio already and what controller board and servos you have? I can try to look up for you how well supported it is right now.

Thanks for the feedback!

There are open source versions of everything done within a GCP API call, but it requires multiple machines and lots of data to build an NLP model to be as fast and accurate as GCP, and cloud computing is relatively new compared to OCR.

Also AFAIK GCV uses techniques beyond better OCR that greatly help accuracy. It does image fixing, boundary detection, NLP, spell check, etc.

But other services don't connect to your friends. So I guess it's more like, paying them not to use any intersecting public roads.

Isn't this sort of like estimating the value of Ford by paying users not to use roads?

underrated post.

Investors care about revenue.

Wrong, it was the best selling overall sedan in US by revenue, including gas cars.

Depends on how you calculate it. Toyota sold more car, but in terms of $$ spent, Model 3 is the most popular sedan in US.

You don't care about profitability anymore?

Now you want to talk about demand? OK.

- Tesla is mentioned in multiple current top rap songs.

- Elon has the most viewed episode of the most viewed podcast.

- Tesla is working on a rocket powered car.

- Teslas are featured in major TV shows and movies.

- $45k auto loan is within range of your average middle class budget.

You think that wont translate to sales? We'll see.

No.