[alnwlsn]

The future: "and I want a 3mm hole in one side of the plate. No the other side. No, not like that, at the bottom. Now make it 10mm from the other hole. No the other hole. No, up not sideways. Wait, which way is up? Never mind, I'll do it myself."

I'm having trouble understanding why you would want to do this. A good interface between what I want and the model I will make is to draw a picture, not write an essay. This is already (more or less) how Solidworks operates. AI might be able to turn my napkin sketch into a model, but I would still need to draw something, and I'm not good at drawing.

The bottleneck continues to be having a good enough description to make what you want. I have serious doubts that even a skilled person will be able to do it efficiently with text alone. Some combo of drawing and point+click would be much better.

This would be useful for short enough tasks like "change all the #6-32 threads to M3" though. To do so without breaking the feature tree would be quite impressive.

[abe_m]

I think this is along the lines of the AI horseless carriage[1] topic that is also on the front page right now. You seem to be describing the current method as operated through an AI intermediary. I think the power in AI for CAD will be at a higher level than lines, faces and holes. It will be more along the lines of "make a bracket between these two parts". "Make this part bolt to that other part". "Attach this pump to this gear train" (where the AI determines the pump uses a SAE 4 bolt flange of a particular size and a splined connection, then adds the required features to the housing and shafts). I think it will operate on higher structures than current CAD typically works with, and I don't think it will be history tree and sketch based like Solidworks or Inventor. I suspect it will be more of a direct modelling approach. I also think integrating FEA to allow the AI to check its work will be part of it. When you tell it to make a bracket between two parts, it can check the weight of the two parts, and some environmental specification from a project definition, then auto-configure FEA to check the correct number of bolts, material thickness, etc. If it made the bracket from folded sheet steel, you could then tell it you want a cast aluminum bracket, and it could redo the work.

[1]https://news.ycombinator.com/item?id=43773813

[jillesvangurp]

It's also going to be about diagnosing issues. "This part broke right here, explain why and come up with a solution", "Evaluate the robustness of this solution", "Can I save some material and reduce the weight", etc.

Those are the kind of high level questions that an LLM with a decent understanding of CAD and design might be able to deal with soon and it will help speed up expensive design iterations.

A neat trick with current LLMs is to give them screenshots of web pages and ask some open questions about the design, information flow, etc. It will spot things that expert designers would comment on as well. It will point out things that are unclear, etc. You can go far beyond just micro managing incremental edits to some thing.

Mostly the main limitation with LLMs is the imagination of the person using it. Ask the right questions and they get a lot more useful. Even some of the older models that maybe weren't that smart were actually quite useful.

For giggles, I asked chatgpt to critique the design of HN. Not bad. https://chatgpt.com/share/6809df2b-fc00-800e-bb33-fe7d8c3611...

[wavefrontbakc]

I think the cost of mistakes is the major driving force behind where you can adopt tools like these. Generating a picture of a chair with five legs? No big deal. Generating supports for a bridge that'll collapse next week? Big problem.

> It will point out things that are unclear, etc. You can go far beyond just micro managing incremental edits to some thing.

When prompted an LLM will also point it out when it's perfectly clear. LLM is just text prediction, not magic

[ben_w]

> I think the cost of mistakes is the major driving force behind where you can adopt tools like these. Generating a picture of a chair with five legs? No big deal. Generating supports for a bridge that'll collapse next week? Big problem

Yes, indeed.

But:

Why can LLMs generally write code that even compiles?

While I wouldn't trust current setups, there's no obvious reason why even a mere LLM cannot be used to explore the design space when the output can be simulated to test its suitability as a solution — even in physical systems, this is already done with non-verbal genetic algorithms.

> LLM is just text prediction, not magic

"Sufficiently advanced technology is indistinguishable from magic".

Saying "just text prediction" understates how big a deal that is.

[wavefrontbakc]

>While I wouldn't trust current setups, there's no obvious reason why even a mere LLM cannot be used to explore the design space when the output can be simulated to test its suitability as a solution

Having to test every assertation sounds like a not particularly useful application, and the more variables there are the more it seems to be about throwing completely random things at the wall and hoping it works

You should use a tool for it's purpose, relying on text prediction to predict clarity is like relying on teams icons being green to actual productivity; a very vague, incidentally sometimes coinciding factor.

You could use text predictor for things that rely on "how would this sentence usually complete" and get right answers. But that is a very narrow field, I can mostly imagine entertainment benefiting a lot.

You could misuse text predictor for things like "is this <symptom> alarming?" and get a response that is statistically likely in the training material, but could be completely inverse for the person asking, again having very high cost for failing to do what it was never meant to. You can often demonstrate the trap by re-rolling your answer for any question a couple times and seeing how the answer often varies mild-to-completely-reverse depending on whatever seed you land.

[ben_w]

> Having to test every assertation sounds like a not particularly useful application, and the more variables there are the more it seems to be about throwing completely random things at the wall and hoping it works

That should be fully automated.

Instead of anchoring on "how do I test what ChatGPT gives me?", think "Pretend I'm Ansys Inc.*, how would I build a platform that combines an LLM to figure out what to make in the first place from a user request, with all our existing suite of simulation systems, to design a product that not only actually meets the requirements of that user request, but also actually proves it will meet those requirements?"

* Real company which does real sim software

[aredox]

>Saying "just text prediction" understates how big a deal that is.

Here on HN we often see posts insisting on the importance of "first principles".

Your embrace of "magic" - an unknown black box who does seemingly wonderful things that usually blow up to one's face and have a hidden cost - is the opposite of that.

LLMs are just text prediction. That's what they are.

>Why can LLMs generally write code that even compiles?

Why can I copy-paste code and it compiles?

Try to use LLM on code there is little training material about - for example PowerQuery or Excel - and you will see it bullshit and fail - even Microsoft's own LLM.

[ben_w]

> Why can I copy-paste code and it compiles?

I think phrasing it like that is called "begging the question": you've already skipped past all the intelligence you had to apply to figure out which part of the entire internet constituted "code".

And not just any code, but code in correct language. If I copy-paste C64 Basic into the middle of a .swift file (and not as a string), it isn't going to compile.

And not just in the correct language, but a complete block of it, rather than a fragment.

> even Microsoft's own LLM.

"even" suggests you hold them in higher regard than I do.

[cdecl]

> LLMs are just text prediction. That's what they are.

This sort of glib talking point really doesn't pass muster, because if you showed the current state of affairs to a random developer from 2015, you would absolutely blow their damned socks off.

[abe_m]

I doubt that an LLM for CAD would be using the free-form generation that seems to lead to the 5-legged chair.

I suspect it will be more of a tool calling layer that is building up the model based on the output of more deterministic tools. "I need this bearing mounted here" -> LLM reads the part number of the bearing, does a RAG search for the bearing properties to get sizes, looks up what type of fits should be used in the scenario, feeds that info into a function that generates the appropriate seat geometry. Rather than trying to morph triangles into sort-of-kind-of a cylindrical face that may or may have the 0.0XXmm interference that is the difference between success or failure of the fitment.

[sharemywin]

isn't it closer to concept prediction layered over top of text prediction because of the multiple levels? it compresses text into concepts using layers of embeddings and neural encoding then predicts the concept based on multiple areas of attention. then decompresses it to find the correct words to convey the concept.

[baq]

The text of every Nobel winning physics theory was predicted in someone’s head, too

[Nevermark]

> Mostly the main limitation with LLMs is the imagination of the person using it. Ask the right questions and they get a lot more useful.

Completely agree.

We get waves of comments on HN downplaying model abilities or their value.

Many people don’t seem to explore and experiment with them enough. I have 3 screens. The left one has two models on it. The right one has a model & a web browser for quick searches. I work on the largest middle screen.

Extreme maybe, but I use them constantly resulting in constant discovery of helpful new uses.

I web search maybe 10% of what I did six months ago.

The quirks are real, but the endless upsides models deliver when you try things were unobtainium, from humans or machines, until LLMs.

[wavefrontbakc]

I've only found useful answers for when I've begun something from completely zero. Things I've got even a reasonable grasp on I start to spot large dangerous holes a model very confidently claims is the right solution. Stuff like bringing camping stove inside a tent to avoid rainy weather, nevermind it being suicide at the same time.

>I web search maybe 10% of what I did six months ago.

Me too, though this is more driven by the total cliff-fall of web search result quality

[sharemywin]

I'm not sure what you used for it to tell you that?

what should I do with my camping stove if I want to avoid the rain

ChatGPT said: If you want to avoid the rain while using your camping stove, here are your best options:

Shelter Options: Use a Tarp: Set up a tarp high above your stove area with good airflow. Make sure it's not enclosed and water runs off away from you.

Camp Kitchen Tent: Lightweight pop-up canopies or dedicated camp kitchen shelters are perfect. Just make sure it’s ventilated.

Picnic Table Shelter: Many campgrounds have covered areas you can cook under — check for those.

Vestibule (Cautiously): If you have a tent with a large vestibule, you can use the stove there, only if it's very well-ventilated and you're extremely cautious (fire and carbon monoxide risks are real).

Important Safety Tips: Never use a stove inside a closed tent — risk of carbon monoxide poisoning and fire.

Keep the stove on a stable, flat surface.

Avoid cooking right under trees with low-hanging branches.

Ensure your shelter is tall enough — heat rises.

Would you like a quick sketch or image of a tarp setup that works well in rain?

[anthonyrstevens]

I'm starting to think that many of the "But the AIs tell me I should drive my car off a cliff!!" posters are just making stuff up.

[cdecl]

The problem I have with this conclusion is that "trust but verify" long predates AI models. People can, and have been, posting total bullshit on the internet since time immemorial. You have never _not_ needed to actually validate the things you are reading.

[dmd]

> Not bad

It reads like a horoscope to me.

[krige]

> Not bad. I'm sorry but it's pretty bad. Hierarchy complaint is bogus, so's navigation overload, it hallucinates BG as white, and the rest is very generic.

[otabdeveloper4]

> wanting AI to make decisions

That's a mega-yikes for me.

Go ahead and do something stupid like that for CEO or CTO decisions, I don't care.

But keep it out of industrial design, please. Lives are at stake.

[alnwlsn]

You're right, but I think we have a long way to go. Even our best CAD packages today don't work nearly as well as advertised. I dread to think what Dassault or Autodesk would charge per seat for something that could do the above!

[abe_m]

I agree. I think a major hindrance to the current pro CAD systems is being stuck to the feature history tree, and rather low level features. Considerable amounts of requirements data is just added to a drawing free-form without semantic machine-readable meaning. Lots of tolerancing, fit, GD&T, datums, etc are just lines in a PDF. There is the move to MBD/PMI and the NIST driven STEP digital thread, but the state of CAD is a long way from that being common. I think we need to get to the data being embedded in the model ala MBD/PMI, but then go beyond it. The definition of threads, gear or spline teeth, ORB and other hydraulic ports don't fit comfortably into the current system. There needs to be a higher level machine-readable capture, and I think that is where the LLMs may be able to step in.

I suspect the next step will be such a departure that it won't be Siemens, Dassault, or Autodesk that do it.

[coderenegade]

I think this is correct, especially the part about how we actually do modelling. The topological naming problem is really born from the fact that we want to do operations on features that may no longer exist if we alter the tree at an earlier point. An AI model might find it easier to work directly with boolean operations or meshes, at which point, there is no topological naming problem.

[seveibar]

Most likely you won’t be asking for specific things like “3mm hole 3in from the side”, you’ll say things like “Create a plastic enclosure sized to go under a desk, ok add a usb receptacle opening, ok add flanges with standard screw holes”

In the text to CAD ecosystem we talk about matching our language/framework to “design intent” a lot. The ideal interface is usually higher level than people expect it to be.

[mediaman]

The problem is that this isn't very useful except for the very earliest ideation stages of industrial design, which hardly need CAD anyway.

Most parts need to fit with something else, usually some set of components. Then there are considerations around draft, moldability, size of core pins, sliders, direction of ejection, wall thickness, coring out, radii, ribs for stiffness, tolerances...

LLMs seem far off from being the right answer here. There is, however, lots to make more efficient. Maybe you could tokenize breps in some useful way and see if transformers could become competent speaking in brep tokens? It's hand-wavy but maybe there's something there.

Mechanical engineers do not try to explain models to each other in English. They gather around Solidworks or send pictures to each other. It is incredibly hard to explain a model in English, and I don't see how a traditional LLM would be any better.

[esperent]

You may or may not be right, but your arguments sound like echos of what software developers were saying four or five years ago. And four or five years ago, they were right.

Don't dismiss an AI tool just because the first iterations aren't useful, it'll be iterated on faster than you can believe possible.

[littlestymaar]

While LLMs are a useful tool for software development, if you try asking them the software equivalent of “Create a plastic enclosure sized to go under a desk, ok add a usb receptacle opening, ok add flanges with standard screw holes” you'll end up with the equivalent of “No the other side. No, not like that, at the bottom. Now make it 10mm from the other hole. No the other hole. No, up not sideways. Wait, which way is up? Never mind, I'll do it myself” a lot.

What works is asking them to implement micro feature that you will specify well enough at first try, not to ask them writing the entire piece of software from top to bottom. The tech is clearly not there yet for the latter.

The main difference between Code and CAD is that code is language you're writing to the machine to execute already, so it's pretty natural to just use a more abstract/natural language to ask it instead of the formal one of code, whereas CAD is a visual, almost physical task, and it's more pleasant to do a task than describe it in depth with words.

[esperent]

> Create a plastic enclosure sized to go under a desk, ok add a usb receptacle opening, ok add flanges with standard screw holes

With vague specifications like these, you'd get garbage from a human too.

What works for software, and I suspect for other technical fields like CAD too, is to treat it like a junior developer who has an extreme breadth of knowledge but not much depth. You will need to take care to clearly specify your requirements.

[littlestymaar]

> With vague specifications like these, you'd get garbage from a human too.

You'll never have better input than this at the beginning of any project from the person that brings the use-case. That's a full job to help them define the needs more accurately. And if you always work with clear specifications it's just because there's someone in front of you that has helped write the spec starting from the loose business requirement.

> You will need to take care to clearly specify your requirements

Yes, but as I discussed above, for such tasks it's going to be very frustrating and less efficient than doing things by yourself. The only reason why you'd accept to go through this kind of effort for an intern is that because you expect him to learn and become autonomous at some point. With current tech, an LLM will forever remain as clueless as it started.

[mediaman]

I've created (small, toy) transformers and also modeled injection molded parts in Solidworks.

There is a really big difference. It's obvious how programming languages can use tokens for an attention mechanism, which gives them excellent ability to have parallelized performance (versus RNNs, the prior way of relating tokens) with much broader ability to maintain coherence.

I don't know the parallel with brep. What are the tokens here? It's a fundamental architectural question.

But unlike four or five years ago for programming, when the attention mechanism was clear with transformers and the answer was, basically, just "scale it up", we don't even really know where to begin here. So assuming some magic is going to happen is optimistic.

It'd be exciting if we could figure it out. Maybe the answer is that we do away with brep and all tree based systems entirely (though I'm a little unclear how we maintain the mathematical precision of brep, especially with curves, which is necessary for machining -- your machinist is going to throw you out if you start giving them meshes, at least for precision work that has anything with a radius).

[eurekin]

I have come across a significant number of non engineers wanting to do, what ultimately involves some basic CAD modelling. Some can stall on such tasks for years (home renovation) or just don't do it at all. After some brief research, the main cause is not wanting to sink over 30 hours into learning basics of a cad package of choice.

For some reason they imagine it as a daunting, complicated, impenetrable task with many pitfalls, which aren't surmountable. Be it interface, general idea how it operates, fear of unknown details (tolerances, clearances).

It's easy to underestimate the knowledge required to use a cad productively.

One such anecdata near me are highschools that buy 3d printers and think pupils will naturally want to print models. After initial days of fascination they stopped being used at all. I've heard from a person close to the education that it's a country wide phenomena.

Back to the point though - maybe there's a group of users that want to create, but just can't do CAD at all and such text description seem perfect for them.

[Animats]

There's a mindset change needed to use a feature tree based constructive solid geometry system. The order in which you do things is implicit in the feature tree. Once you get this, it's not too hard. But figuring out where to start can be tough.

I miss the TechShop days, from when the CEO of Autodesk liked the maker movement and supplied TechShop with full Autodesk Inventor. I learned to use it and liked it. You can still get Fusion 360, but it's not as good.

The problem with free CAD systems is that they suffer from the classic open source disease - a terrible user interface. Often this is patched by making the interface scriptable or programmable or themeable, which doesn't help. 3D UI is really, really hard. You need to be able to do things such as change the viewpoint and zoom without losing the current selection set, using nothing but a mouse.

(Inventor is overkill for most people. You get warnings such as "The two gears do not have a relatively prime number of teeth, which may cause uneven wear.")

[phkahler]

>> I have come across a significant number of non engineers wanting to do, what ultimately involves some basic CAD modelling.

I very much want Solvespace to be the tool for those people. It's very easy to learn and do the basics. But some of the bugs still need to get fixed (failures tend to be big problems for new users because without experience its hard to explain what's going wrong or a workaround) and we need a darn chamfer and fillet tool.

[Animats]

> I very much want Solvespace to be the tool for those people.

Probably not. "Copyright 2008-2022 SolveSpace contributors. Most recent update June 2 2022."

[phkahler]

Most recent commit to the repository: Last week. It's slow and has slowed the last couple years but it's still going.

[itissid]

> and I want a 3mm hole in one side of the plate. No the other side. No, not like that, at the bottom. Now make it 10mm from the other hole. No the other hole. No, up not sideways.

One thing that is interesting here is you can read faster than TTS to absorb info. But you can speak much faster than you can type. So is it all that typing that's the problem or could be just an interface problem? and in your example, you could also just draw with your hand(wrist sensor) + talk.

As I've been using agents to code this way. Its way faster.

[alnwlsn]

Feels a bit like being on a call with someone at the hardware store, about something that you both don't know the name for. Maybe the person on the other end is confused, or maybe you aren't describing it all that well. Isn't it easier to take a picture of the thing or just take the thing itself and show it to someone who works there? Harder again to do that when the thing you want isn't sold at the store, which is probably why you're modeling it in the first place.

Most of the mechanical people I've met are good at talking with their hands. "take this thing like this, turn it like that, mount it like this, drill a hole here, look down there" and so on. We still don't have a good analog for this in computers. VR is the closest we have and it's still leagues behind the Human Hand mk. 1. Video is good too, but you have to put in a bit more attention to camerawork and lighting than taking a selfie.

[voidUpdate]

And I can think faster than I can speak, which means it's easier for me to think about what I need to do and then do it, rather than type or speak to an LLM so they can work out what I need to do instead

[michaelt]

> I'm having trouble understanding why you would want to do this.

You would be amazed at how much time CAD users spend using Propriety CAD Package A to redraw things from PDFs generated by Propriety CAD Package B

[plorg]

I spend a lot of time using proprietary CAD package A to redraw things from Who Knows What, but that's mostly because the proprietary CAD data my vendor would send me is trapped behind an NDA for which getting legal approval would take more time and effort than just modeling the things in front of me with minimum viable detail, or else my vendor is 2 businesses removed from the person with the CAD data that I need (and may require a different NDA that we can't sign without convincing our vendor to do the same). Anyone I've ever been able to request CAD data from will just send me STEP or parasolid files and they will work well enough for me to do my job. Often I spend more time removing model features so my computer will run a little faster.

[whatshisface]

Here's how it might work, by analogy to the workflow for image generation:

"An aerodynamically curved plastic enclosure for a form-over-function guitar amp."

Then you get something with the basic shapes and bevels in place, and adjust it in CAD to fit your actual design goals. Then,

"Given this shape, make it easy to injection mold."

Then it would smooth out some things a little too much, and you'd fix it in CAD. Then, finally,

"Making only very small changes and no changes at all to the surfaces I've marked as mounting-related in CAD, unify my additions visually with the overall design of the curved shell."

Then you'd have to fix a couple other things, and you'd be finished.

[zonkerdonker]

I appreciate that you have given this some thought, but it is clear that you dont have much or any professional experience in 3D modeling or mechanical design.

For the guitar amp, ok. Maybe that prompt will give you a set of surfaces you can scale for the exterior shell of the amp. Because you will need to scale it, or know exactly the dimensions of your speakers, internal chambers, electronics, I/O, baffles, and where those will all ve relative go eachother. Also...Do you need buttons? Jacks/connectors/other I/O? How and where will the connections be routed to other components? Do you need an internal structure with an external aesthetic shell? Or are you going to somehow mold the whole thing in one piece? Where should the part be split? What kind of fasteners will join the parts and where should they be joined? What material is the shell? Can it be thinner to save weight? Or need ribs or thickness for strength? Where does it need to be strong?

These are the issues from 30 seconds of thinking about this. AI (as suggested) could maybe save me from surfacing an exterior cosmetic cover, given presice constraints and dimensions, but at that point, I may as well just do it myself.

If you have a common, easy, already solved an mechanical design problem (hinge e.g.), then you buy an off the shelf component. For everything else, it is bespoke, and every detail matters. Every problem is a "wine glass full to the brim"

[throwup238]

I think you’re jumping too fast to the “vibe CADing” extreme. It’s been a while since I’ve used Solidworks in anger so I’d rather use ECAD as an example: I’d kill for the ability to give Altium a PDF datasheet and have it generate footprints or schematic components tailored to my specific pinout for a microcontroller. Or give it a pdf of routing guidelines and have it convert those to design rules tied just to those nets. Those are the details that take up most of the time (although I’d still spend quite a lot of tine verifying all the output).

In MCAD it’s less of a problem because all the big vendors like Misumi, McMaster, et al have extensions or downloadable models but anything custom could probably benefit from LLMs (I say this as someone who is generally skeptical of their vision capabilities). I don’t think vibe CADing will work because most parts are too parametrized but giving an AI a bunch of PDFs and a size + thickness is probably going to be really productive.

[tylergetsay]

In your example, what about mounting the electronics or specifying that the control knobs need to fit within these dimensions? I guess its easy if those objects are available as a model, but thats not always the case.. 3d scanner maybe?

[whatshisface]

You'd get control knobs of a reasonable size, and mounting holes in an arbitrary rectangle, then correct them with the true dimensions outside of generation.

[ssl-3]

So maybe the future is to draw a picture, and go from there?

For instance: My modelling abilities are limited. I can draw what I want, with measurements, but I am not a draftsman. I can also explain the concept, in conversational English, to a person who uses CAD regularly and they can hammer out a model in no time. This is a thing that I've done successfully in the past.

Could I just do it myself? Sure, eventually! But my modelling needs are very few and far between. It isn't something I need to do every day, or even every year. It would take me longer to learn the workflow and toolsets of [insert CAD system here] than to just earn some money doing something that I'm already good at and pay someone else to do the CAD work.

Except maybe in the future, perhaps I will be able use the bot to help bridge the gap between a napkin sketch of a widget and a digital model of that same widget. (Maybe like Scotty tried to do with the mouse in Star Trek IV.)

(And before anyone says it: I'm not really particularly interested in becoming proficient at CAD. I know I can learn it, but I just don't want to. It has never been my goal to become proficient at every trade under the sun and there are other skills that I'd rather focus on learning and maintaining instead. And that's OK -- there's lots of other things in life that I will probably also never seek to be proficient at, too.)

[wgpatrick]

Yeah - I fully agree with this POV. From a UX/UI POV, I think this is where things are headed. I talk about this a bit at the end of the piece.

[chpatrick]

If the napkin sketch generation is 95% right and only needs minor corrections then it's still a massive time saver.

[wilg]

Think about it this way, if the richest person in the world wanted something done, they would probably just shoot off a text to someone, maybe answer a few questions, and then some time later it would be done. That's your interface.

[bboygravity]

Text (specs + conversations) is the starting point of 100 percent of all CAD drawings made by more than 1 human though (so essentially everything you see around you).

I don't get your point (and yes I use CAD programs myself).

[alnwlsn]

Most of the things I work on are "make this fit onto that like this". There's not that much information contained in that sentence, it's contained in the 2 objects I was just handed. Sometimes we have drawings for that stuff, most of the time we don't. The "like this" part can be a conversation, but the rest of the info is missing and needs to be recreated.

I said this below, but most of the mechanical people I've met are good at talking with their hands. "take this thing like this, turn it like that, mount it like this, drill a hole here, look down there" and so on. We still don't have a good analog for this in computers. VR is the closest we have and it's still leagues behind the Human Hand mk. 1. Video is good too, but you have to put in a bit more attention to camerawork and lighting than taking a selfie.

[fragmede]

talking to my computer and having it create things is pretty danged cool. Voice input takes out so much friction that, yeah, maybe it would be faster with a mouse and keyboard, but if I can just talk with my computer? I can do it while I'm walking around and thinking.

[oofbaroomf]

If you would use LLM-assisted CAD for real industrial design, you would have to end up by specifying exactly where everything has to go and what size it has to be. But if you are doing that then you may as well make an automated program to convert those specific requirements into a 3D model.

Oh wait, that's CAD.

Cynical take aside, I think this could be quite useful for normal people making simple stuff, and could really help consumer 3D printing have a much larger impact.

[lud_lite]

If there I in AI then it would tell me where to put the hole and why.