I tried this a few months back with claude 3.5 writing cadquery code in cline, with render photos for feedback. I got it to model a few simple things like terraforming mars city fairly nicely. However it still involved a fair bit of coaching. I wrote a simple script to automate the process more but it went off the rails too often.
I wonder if the models improved image understanding also lead to better spatial understanding.
Makes you wonder if there is a place in the pipeline for generating G-code (motion commands that run CNC mills, 3d printers etc.)
Being just a domestic 3d printer enthousiast I have no idea what the real world issues are in manufacting with CNC mills; i'd personally enjoy an AI telling me which of the 1000 possible combinations of line width, infill %, temperatures, speeds, wall generation params etc. to use for a given print.
There is some industry usage of AI in G-code generation. But it often requires at least some post processing. In general if you just want a few parts without hard tolerances it can be pretty good. But when you need to churn out thousands it's worth it to go in an manually optimize to squeeze out those precious machine hours.
Really cool, I'd love to try something like this for quick and simple enclosures. Right now I have some prototype electronics hot glued to a piece of plywood. It would be awesome to give a GenCAD workflow the existing part STLs (if they exist) and have it roughly arrange everything and then create the 3D model for a case.
Maybe there could be a mating/assembly eval in the future that would work towards that?
About a year ago I had a 2D drawing of a relatively simple, I uploaded it to chatgpt and asked it to model it in cadquery. It required some coaching and manual post processing but it was able to do it. I have since moved to solvespace since even after using cadquery for years I was spending 50% of the time finding some weird structure to continue my drawing from. Solvespace is simply much more productive for me.
I've done this, and printed actual models AIs generated. In my experience Grok does the best job with this - it one shots even the more elaborate designs (with thinking). Gemini often screws up, but it sometimes can (get this!) figure things out if you show it what the errors are, as a screenshot. This in particular gives me hope that some kind of RL loop can be built around this. OpenAI models screw up and can't fix the errors (common symptom: generate slightly different model with the same exact flaws). DeepSeek is about at the same level at OpenSCAD as OpenAI. I have not tried Claude.
Typically only the most powerful models are worth a try and even then they feel like they aren't capable enough. This is not surprising: to the best of my knowledge none of the current SOTA models was trained to reason about 3D geometry. With Grok there's just one model: Grok3. With OpenAI I used o1 and o3 (after o3 was released). With Google, the visual feedback was with Gemini Pro 2.5. Deepseek also serves only one model. Where there is a toggle (Grok and Deepseek), "thinking" was enabled.
I tried this a few months back with claude 3.5 writing cadquery code in cline, with render photos for feedback. I got it to model a few simple things like terraforming mars city fairly nicely. However it still involved a fair bit of coaching. I wrote a simple script to automate the process more but it went off the rails too often.
I wonder if the models improved image understanding also lead to better spatial understanding.
Makes you wonder if there is a place in the pipeline for generating G-code (motion commands that run CNC mills, 3d printers etc.)
Being just a domestic 3d printer enthousiast I have no idea what the real world issues are in manufacting with CNC mills; i'd personally enjoy an AI telling me which of the 1000 possible combinations of line width, infill %, temperatures, speeds, wall generation params etc. to use for a given print.
There is some industry usage of AI in G-code generation. But it often requires at least some post processing. In general if you just want a few parts without hard tolerances it can be pretty good. But when you need to churn out thousands it's worth it to go in an manually optimize to squeeze out those precious machine hours.
Really cool, I'd love to try something like this for quick and simple enclosures. Right now I have some prototype electronics hot glued to a piece of plywood. It would be awesome to give a GenCAD workflow the existing part STLs (if they exist) and have it roughly arrange everything and then create the 3D model for a case.
Maybe there could be a mating/assembly eval in the future that would work towards that?
About a year ago I had a 2D drawing of a relatively simple, I uploaded it to chatgpt and asked it to model it in cadquery. It required some coaching and manual post processing but it was able to do it. I have since moved to solvespace since even after using cadquery for years I was spending 50% of the time finding some weird structure to continue my drawing from. Solvespace is simply much more productive for me.
I've done this, and printed actual models AIs generated. In my experience Grok does the best job with this - it one shots even the more elaborate designs (with thinking). Gemini often screws up, but it sometimes can (get this!) figure things out if you show it what the errors are, as a screenshot. This in particular gives me hope that some kind of RL loop can be built around this. OpenAI models screw up and can't fix the errors (common symptom: generate slightly different model with the same exact flaws). DeepSeek is about at the same level at OpenSCAD as OpenAI. I have not tried Claude.
You've got to be a bit more specific, those words can all refer to many models.
Typically only the most powerful models are worth a try and even then they feel like they aren't capable enough. This is not surprising: to the best of my knowledge none of the current SOTA models was trained to reason about 3D geometry. With Grok there's just one model: Grok3. With OpenAI I used o1 and o3 (after o3 was released). With Google, the visual feedback was with Gemini Pro 2.5. Deepseek also serves only one model. Where there is a toggle (Grok and Deepseek), "thinking" was enabled.
Wow! As someone that's written openscad scripts manually I can get real excited about this.
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