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A note that Aerospace has absolutely leaned into 3D printing metal parts since they can make parts much lighter and be just as strong.
The main use of LLMs, as far as I can see, is to replace the very people pushing it on everyone.
That's about being willing to eat the nre for one-off special purpose parts that have geometries not attainable by casting or machining.
3d printing is not the default fabrication method now that we're getting good at it. It just shines in certain applications.
AI is often pitched as being able to do anything, eventually. We even try to use passive fail safes over active ones, a century after electricity became commonly available. Because that will always be a better solution by the nature of the options. AI is the same way. It is a distillation of human English language that is written. Why you would think that that could eventually replace all software developers, or any other field that produces text as its output makes any sense is beyond me. I can't see how that could be true.
3d printing is not the default fabrication method now that we're getting good at it. It just shines in certain applications.
Getting a little theoretical here
With the current state of the technology, 3d printing lags behind some traditional manufacturing techniques like machining and in terms of speed, cost, quality, available materials, etc. except for some relatively niche cases.
However, that gap is closing a bit every day, it may or may not ever catch up completely or surpass the old technique in those aspects
But if it does ever get close, I could very much see 3d printing being a preferred method
Subtractive manufacturing like machining, by design, creates a lot of waste, all of the chips and off cuts that are removed from the stock are either discarded or require additional energy and/or materials to recycle.
And things like injection molding require custom molds that wear out over time, and can be expensive to design and manufacture
And in either case, you're largely locked into making one thing on an assembly line at a time, and to switch over to a different product you're probably going to need to switch out a lot of the molds and tooling, recalibrate everything, etc. which can be time consuming.
With 3d printing, you could theoretically use only the amount of material that's actually in the finished product (if you design it that it doesn't require any external supports ) you don't need any custom tooling or mold, just generic, interchangeable nozzles (for FDM, LCD screens or lasers or whatever the equivalent is for other printing technologies) and you could switch production from one item to another by just hitting print on a different file.
Again, we're not there, may never be there, but it's a cool thing to think about
Exactly. It's not true. Any company that fires all of its developers and sets up some poor intern to prompt-engineer updates to their codebase is going to fail spectacularly.
Source: I'm a software developer and use LLMs regularly. There are certain tasks they are very good at, but anyone who commits unexamined code generated by an LLM gets exactly what they deserve.
Ok, im a hardware dev. They've tried to make us do software style project management every time there's a new fad (agile last time). It usually doesn't fit.
What do you find them useful for in your role? Like a coding partner, you can ask questions? Or linting? Im at a loss in my role. I need to know the proprietary code base to write a single line of value. We aren't allowing anyone to train an ai on our code. Thats a huge security problem if anyone does.
So there are a few very specific tasks that LLMs are good at from the perspective of a software developer:
- Certain kinds of analysis tasks can be done very quickly and efficiently with Copilot in agent mode. For instance, having it assess your existing code for adherence to stylistic standards where a violation isn't going to trigger a linting error.
- Quick script writing is something it excels at. There are all kinds of circumstances where you might need an independent script, such as a database seed file. It's not part of the application itself, but it's a useful utility to have, and Copilot is good at writing them.
- Scaffolding a new application. If you're creating something brand new and know which tools you want to use for it, but don't want to go through the hassle of setting everything up yourself, having Copilot do it can be a real time saver.
And that's... pretty much it. I've experimented with building applications with "prompt engineering," and to be blunt, I think the concept is fundamentally flawed. The problem is that once the application exceeds the LLM's context window size, which is necessarily small, you're going to see it make a lot more mistakes than it already does, because - just as an example - by the time you're having it write the frontend for a new API endpoint, it's already forgotten how that endpoint works.
As the application approaches production size in features and functions, the number of lines of code becomes an insurmountable bottleneck for Copilot. It simply can't maintain a comprehensive understanding of what's already there.
They are getting faster, having larger context windows, and becoming more accurate. It is only a matter of time until AI simply copy-cats 99.9% of the things humans do.
Actually, there's growing evidence that beyond a certain point, more context drastically reduces their performance and accuracy.
I'm of the opinion that LLMs will need a drastic rethink before they can reach the point you describe.
We have 100M context AI, we just need better attention mechamisms.
Yea, should say: FDM 3D printing a screw with PLA vertically in vase mode.
But thats a bit long winded.
I 3d print screws all the time. They are fine for many uses.
One of the first things I did with my 3D printer was create wood screws - as in, screw made out of wood plastic. Fun pocket giveaway.
You "nailed down" screws? I think that's your problem. You are supposed to hold the screw with a wrench and then rotate the entire piece of wood around it. What an idiot.
On a serious note. That is absolutely how I feel about LLMs. For one, LLMs are a specific subset of ML, which is itself a subset of a full "AI". I hate that LLM has been branded AI when that is completely misleading at best and a flat out lie at worst. Sure it's a part of AI, but it's like marketing a steering wheel as a whole car. It's very useful as a tool for a specific job, but saying it's a car makes people think it's all they need to travel somewhere.
LLMs are really just "Google Search 2.0" it just scrapes all the sites and combines them into a somewhat more concise and useful answer, but since anyone can post anything on the internet and those things can be true or false or anything in between, so too will the answers LLMs provide you. It's risky to put ANY stake in the answers without knowledge yourself of what it means.
You know what? Search engines have become all but useless. I've been happy to let ChatGPT comb through the net for me. The other day I spent a good two hours searching for one single dimension for a pretty common item. I was on the verge of tears, when I asked Chat GPT and got the answer in 10 seconds, and a confirmation that most sources just skip it.
Stract.com just links to content like pre 2010 google.
this post was submitted on 31 Aug 2025
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Showerthoughts
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A "Showerthought" is a simple term used to describe the thoughts that pop into your head while you're doing everyday things like taking a shower, driving, or just daydreaming. The most popular seem to be lighthearted clever little truths, hidden in daily life.
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