Spectral Labs Releases Sgs-1: the First Generative Model for Structured Cad
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Spectral Labs releases SGS-1, a generative model for structured CAD, sparking discussion on its potential impact on design and manufacturing, as well as concerns about its accuracy and usability.
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The difficult part is the manufacturing, also coming up with the plausible load paths and deciding on the geometry of the parts according to the actual loads.
> also coming up with the plausible load paths and deciding on the geometry of the parts according to the actual loads
It would help with that as well.
Have you even used it and know if it does what it claims?
Sorry, you can't confirm shit.
Beyond having a cad file where there wasn’t one… how?
This is a game changer, all the models before that output meshes were a toy at best. Super excited to see where they can take this.
I wander if the next step is for a step -> proprietary format (SolidWork, NX etc) model that can infer constraints.
There are so many hobbyist 3D printing things I’d like to do around my abode by taking some existing piece and tweaking it. Creating a model for a one off part is pretty tedious though.
Designing something that has the right features is easy, the hard part is creating a design that is manufacturable, fits inside the allocated space, has the desired mechanical properties (e.g. rigidity) at the desired cost (uses less material, is easy to manufacture).
As an example, parts for 3D printing have various design constraints, as you want to avoid support material and want to print the part in a certain orientation. Being able to verbally tell an AI model to incorporate these constraints would be very beneficial.
Also to generate clean 3D meshes from points cloud, while identifying the various objects via the colours/lighting. That would be also really interesting. It could as well describe the world, and the object's meta data.
As for something like this, it removes the fun of CAD design more than solve a problem, I think we best focus AI for repetitive boring tasks, rather than design. This may wow investors, and may save professional minutes, but it does not really solve the bigger problems.
<Insert meme about AI doing arts while we still do the dishes />
When I was nude drawing, the first few poses were always very short (half a minute or a minute) and towards the end of a session the poses took longer. Forcing the brain to make quick decisions (and yes, err along the way) is a fantastic method to force the brain to learn, the sense of urgency and the sense of importance are very much related.
Reflexive / reaction speed computer games force a player to learn.
I believe its possible to upload neural network weights to the human brain by reaction speed games.
I agree with your assessment of the driving force behind machine learning (laying off workers), but I believe it will usher in a new Enlightenment era, where the tremendous energy intensive computations to summarize human knowledge into a compressed form of neural weights results in the democratization of all this knowledge (and if those MBA's had this foresight, they wouldn't share those weights at all! unless they secretly "fight babylon from the inside out").
I will soon try this on a smaller model (that has basic ~100-language knowledge).
The main issues are transforming the model weights so that all weights are embedding weights (moving the attention and feed-forward weights to token weights), but this requires knowledge distillation, and I know what form I want, but not sure if I have the requisite compute to do it.
The second issue is figuring out how many weights per day one can learn.
“Connect these two parts”, “add screw holes here”, “make a snap fit joint”, “make it 8cm wide”, “move these holes to the other side” is what I dream of!
This is obviously a lie without even testing it. STEP files do not have any sort of support for parametric features.
> SGS-1 outputs are accurate and can be edited easily in traditional CAD software.
I tested this on their own demo file to give it its best chance at working correctly and this claim they've made is just a complete lie. I've included the input and output for comparison below next to a correct part I modelled myself[1][2] and a list of errors. These aren't just incorrect dimensions but broken features that make these very hard to edit.
I don't know why they'd lie about this and them provide a demo the shows they're lying with their own input files, and even text on their own page which makes a claim that can not be true based solely on the information further down that page. Is it to get news headlines? Do they want to sell this to people that don't know any better? Is this simply just another case of CS people thinking they've solved a problem without having any domain knowledge to know their claims are nonsense?
- Every dimension is wrong aside from the one that I corrected to get the same scale (there doesn't appear to be any correct relative to each-other which is why I just picked one at random)
- One hole doesn't go all the way through
- The closest hole isn't round (it's two holes with slightly different diameters that overlap with a sum larger than either hole)
- The fillets are not fillets
- The top hole is offset
- The front chamfer goes down past the base
- The not-fillets don't have the same radius
- The two top holes are offset from each other in Z
- The front chamfer is joined to the circle in different ways on each side (to be fair the drawing is nonsensical here, I just went for a tangent with the circle on my part)
- Much more that I've probably missed
[1]: https://files.catbox.moe/mzb9bb.png
[2]: https://files.catbox.moe/5xkna1.png
Yes, this is also confusing me to no end. How can they make such a claim? They even explicitly state that they generate a B-rep (boundary representation) output only, then in their roller example they say "as the output is parametric, dimensions can easily be adjusted." Erm, no? I'd rather model it again with the proper feature history tree and constraints instead of fiddling with a step file.
https://altair.com/inspire
It identifies features as such even from step.
I would be very interested to get a comparison from someone who understands the terrain.
The kernel is not robust to the stupid things I naively ask it to do. Often my code makes sense to me, but OpenSCAD refuses to create an object.
Performance falls off a cliff. You can work around it by pausing previews and adjusting resolution, but that’s a big UX compromise.
Still, I’ve tried a few other options and keep cycling back to OpenSCAD. The barrier to entry is very low, coding AI does a pretty good job, and there’s a decent ecosystem of community modules.
By the time you get done explaining the meaning of your schema, you might have run out of context. Not that it would matter either way. I've never seen the attention mechanism lock onto more than ~10 hard constraints at a time.
Not everything must be done via LLMs themselves. You could use one or more tools to help generate parts of the query.
You might be interested in this:
https://www.pedronasc.com/articles/lessons-building-ai-data-...
Yes, it would seem post hoc feature tree requires the constraints that come from context in your head, but I could imagine that for most cases a "drafter's intuition" in AI may be sufficient, and you could build an interface to allow that to be mostly given up front and then through iterate post generation.
I could imagine the stepwise approach may allow AI training to be more constrained / efficient that trying to do the whole thing in one go.
I bet somebody in the comments will also say it works for them and then provide vague or not details at all.
> can generate fully [...] parametric 3D geometry. >> This is obviously a lie without even testing it. STEP files do not have any sort of support for parametric features.
This is a simple misunderstanding/semantic issue. We aren't trying to misrepresent anything, we (and some others in the research community) interpret parametric as "being composed of primitives with parameters". We have an internal representation we don't expose to users, and we convert that to a B-Rep STEP file which we do expose.
>> Every dimension is wrong aside from the one that I corrected to get the same scale (there doesn't appear to be any correct relative to each-other which is why I just picked one at random)
Visually this output looks close. There are some gaps, but looking at your screenshot, features like the main hole going all the way through are underdetermined. It's very hard for a model to know because even if the hole did not go through the input would look the same. All of this can be fixed by having richer input conditions, and we are actively working on this for SGS-2
>Yes, this is also confusing me to no end. How can they make such a claim? They even explicitly state that they generate a B-rep (boundary representation) output only, then in their roller example they say "as the output is parametric, dimensions can easily be adjusted." Erm, no? I'd rather model it again with the proper feature history tree and constraints instead of fiddling with a step file.
SGS-2 will include a feature tree representation, so this should be more easily editable than this (which should already be easily editable in many cases as well with direct modeling). Several engineers already work with STEP files in their work for to the best of my knowledge.
Thanks once again for all the feedback! We are incorporating all this into our next model.
No officer I wasn't speeding, I have an internal definition of velocity that you don't have access too and it doesn't say I was speeding
Well guess what? You're wrong.
Yes, STEP files don't have a feature tree and cannot be parameterized. I read it as OP saying that under the hood there __is__ parameterization before the final export to STEP.
This means that they could expose this in the future, say if they chose to output to FreeCAD FCStd or even some proprietary format like Solidworks (via $$$ CAD translator packages).
This is just my read - I'm not affiliated and have no internal knowledge to Spectral or SGS-1, but I have worked deep in building CAD plug-ins and custom software for manufacturing automation.
All that said, the demo model quality has issues and many are unmanufacturable (with subtractive means at least) - so there's still along way to go. But I don't think the presentation of their capabilities is disingenuous.
Congrats on the launch of v1, keep going!
You are saying that it does some things. Literally everyone who could ever want to pay you money to use this or future models are going to try it, see that it does not appear to do what they expect for those things, and then:
1. Not want to pay you money
2. Be much harder to attract again in the future. Once bitten, twice shy.
This seems like a bad plan?
however, the output of the current SGS-1 model leaves a lot to be desired in terms of usability and manufacturability.
as sir liam powell so explained, the STEP generated is indeed a STEP file in the fact that it will load on your CAD of choice (CATIA, NX) but it's not even close to being useful for the designer/engineer/fabricator much less a factory or even a 3d printer.
Most importantly: -Surfaces are not G1, G2, or even G0 (un-CAE-able and un-manufacturable) -simple shapes are hyper overcomplicated (a fillet turns into 10++ surfaces mashed together) -and most unfortunately in one part I generated, the output was a collection of separate STEP child parts (meaning, when importing, your single "part" is actually a product containing 10000+ child parts)
looking forward to V2, keep it coming
shameless plug: my entire career has been in CAD and that is why I started Transfigure. to eliminate my own job as a CAD monkey: and get on with the engineering. already having anticipated the limitations which SGS-1 is dealing with, Transfigure's AI architecture is approaching the problem from the perspective of a mechanical engineer whose customers rely on clean data, ready for simulation and manufacturing. because if I submitted data generated by SGS-1 to our fab shop... I would be fired.
yo@xfgr.ai
posting random "artistic" snapshots of various aspects of Transfigure (instagram: itstransfigure) if you care to follow.
without saying too much, the competitive advantage is in training data and I think that will be the deciding factor as to whether or not a company is successful in (Transfiguring? rezzing? summoning?) a real part from a sketch, that can be made into physical stuff, without looking like shapenet cartoons.
I have had moderate success describing things as geometric primitives. I.e. making a simple phone stand is hard to one shot. Had to do it in steps as make a plane with XYZ dimensions, rotate it X degrees up, calculate the height using trig, create another plane with that height, translate to X position. Etc.
Building models in code like this is really cool; it’s great to be able to import, for example, a “gears” library and automatically generate the geometry for complex bevel gear setups. I’ve seen this approach used for more than CAD too; there’s a Python library (GDSFactory) for building photonic ICs in code as well, and I’m sure plenty more.
This workflow is a big motivator for my data notebook project (https://mnty.sh/#serenity), since I would like to build everything for a project in code and have visualizers for each component in one notebook.
* https://github.com/jabberjabberjabber/openscad-mcp
There’s tons of old drawings but lacking measurements or something. The engineer knows how tall it is or what the overall dimensions are so they can easily use that to create a box and tell AI, make this part that fits this thing. This is going to change everything.
3D printing, restorative, imagineering, part manufacturing, everywhere where there is CAD…
https://github.com/ricksher/ASimpleMechatronicMarkupLanguage
In any case, hopefully it anticipated some future company’s would-be IP thereby ensuring Freedom-to-Operate for future open source hardware tinkerers.