Why can AI generate Super Mario but not a wedge ramp for my robot vacuum?
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zzhuchaokn about 4 hours ago 6 comments
DE version is available. Content is displayed in original English for accuracy.
I've been puzzled by something: AI generation can produce an elaborate
figurine, a cartoon character, even a convincing Super Mario — yet it
can't reliably make a simple wedge ramp so my robot vacuum can climb a
step.
For context: I bought a Bambu P2S but can't model. I tried the "describe
it and get a model" AIs — the output is unusable, you can't adjust it,
it's never quite what I meant. I tried having an agent write Python to
build geometry directly — it tops out at simple primitives.
What finally worked: geometric decomposition. I break a complex part into
ordered, grouped steps, describe each as a small spec, and let an agent
execute them in Blender (via blender-mcp). That process turned out to
abstract into a small engine — the key insight being it converts the 3D
spatial reasoning LLMs are bad at, into the structured code they're good
at. I wrote it up here: https://github.com/zhuchaokn/spec-3d-model
My questions:
- Why is "functional part" generation so much weaker than
"figurine/aesthetic" generation? Is it data (no parametrized-CAD training
sets), representation (mesh vs B-rep), or evaluation (nobody benchmarks
"does it print / is it watertight")?
- Is "turn 3D modeling into code for an LLM" the right framing, or am I
missing something better?
Discussion (6 Comments)Read Original on HackerNews
either way, give an actual CAD program like fusion a go. No, not the FOSS stuff- the real stuff. Although, some of them are "close, but no cigar" these days. Not like gimp which is an exercise in self-flagellation.
Because it’s parametric design as opposed to modeling, it inherently lends itself to making it easier to build.
Use metric units when prompting, and Ive even drawn sketches to add to context, and be surprised at how good the outcome can be!