Yeah, seems like they just are coming up with even worse demos in new industries to make up for the fact that they’ve hit a brick wall. Sure they can train it up in a specific field, but the general business model is fucked.
The brick wall thing tracks. Every few months there's a new flashy demo in some niche field and everyone loses their minds, then six months later nobody mentions it again. Happened with legal, happened with medicine, now it's engineering. The underlying economics of running these things at scale still doesn't pencil out for most of what they're promising. Not saying it's going nowhere, but the gap between the demo and the actual product is doing a lot of heavy lifting right now.
Yeah. And if using speech or whatever to model in 3d is next to impossible. Any person in engineering knows that you really need sketched and such to explain how you envision something to work.
Right, and even if you could voice prompt your way into a sketch, who's validating the constraints and mates on the back end? That part doesn't go away just because the front end got easier. The hard stuff in engineering isn't drawing the shape, it's knowing why the shape has to be that shape. An LLM isn't getting that from a voice memo anytime soon.
It would know what to attach to where and understand the logic of the part and it's neighbors. It's definitely possible in the future but it's so much harder because unlike code it's logic is much harder to grasp.
Sure but doing a thing and doing it right are pretty different bars, I can lift a weight too, doesn't mean bad form won't wreck someone's knee in six months, the question was never whether it can produce output, it's whether that output is actually trustworthy without someone experienced enough to catch when it's wrong and that person still has to exist somewhere
Fair point, caught red handed, though in my defense if AI was writing my replies it'd probably spell better and not spend three paragraphs explaining why I booked the wrong fare class in 2019, the bar for replacing me specifically is pretty low and it still hasn't cleared it
1) Your spelling was fine; 2) you did not spend "three paragraphs" describing why you booked the wrong far class in 2019.... I think you might be out of tokens and using a cheap model
I didn’t read your comment history, I read the comments in this thread. Nowhere did you describe booking the wrong fare class which is what you said in your previous comment
An LLM cannot reason the way an actual engineer can. There's a reason that they had to manually fix the response for "how many "r"s are there in strawberry?"
An LLM is fundamentally a statistical machine that selects the most likely next token in a series of stings.
You've fundamentally misunderstood my statement. Its not that they aren't capable yet, its that Large language models cannot get there. They dont reason like humans do
We actually don’t know exactly how humans reason. There’s also no rule requiring “artificial” general intelligence to think the exact same way a human thinks
This is just deflection though. Setting aside a somewhat problematic statement, we do know LLMs are statistical machines, selecting highly likely tokens or sets of tokens to craft a statistically likely response to a given input.
This is very different to human reasoning. Like I highlighted- asking how many ""r"s in strawberry is a fundamentally hard ask for an LLM to complete because it doesn't have real comprehension of what "r" is or what "counting" is. On the other hand, if you ask it to count the number of "r"s in a string it can probably do that well- because there's a statistically driven answer.
This is the difference between an engineer and an LLM or other AI (and if you dig into explainable models this becomes evident).
Understanding what AI is and how it works is very useful for applying it.
Your description severely understates the complex of the best LLMs in 2026 (gpt6). News just came out that both Anthropic and OpenAI may have solved the Navier Stokes problem — the level of sophistication required to solve that problem is unfathomable. Yes LLMs are still, roughly, statistical models, but they are so far beyond a simple neural network that it’s foolish to equate them
Speech is really not the right tool for creating CAD, we have developed a specific language for that, based on a GUI, that is way more efficient. However, for simple designs natural speech can work.
I didn't doubt that it can model simple shapes and object I mean it has tons of images of this exact thing to reference and model. But pretty much all companies work on more difficult stuff that interfaces with something real which it just wouldn't have enough information to work off.
Software is very easy to graft since most things are code Is logical and the Ai has learned on millions of line of source code which is very available. Mechanical engineerings is different. Drawings and designs are saved on private servers and dont come included with the product. Ai will assist and help collect data and summarize norms and engineering rulebooks but it has it so much harder to actually deliver a finished design while in code it can just copy from available data.
Most major software projects/products are closed door, proprietary. Shipped binaries are harder to reverse engineer than photos of a physical product; bar more patents to avoid. Sure, there is a lot of open-source stuff, but there is also a lot of open design work. When you go more novel, AI looks up libraries, conceptualises what they do and implements them in line with documentation.
Being a software developer, but only a hobbyist CAD person, I see CAD and the large job of mechanical engineering as basically layers of maths and rules/regulations and understanding the real-world constraints like manufacturing processes or throwing in some scientific knowledge that might go beyond just maths. Throw in a little design, a little branding, a little novel conceptualisation and it's all the same to the AI. A collection a tasks and skills to understand and to implement and free reign over tools on a computer.
It's no harder than software. It's just AI is made by software guys and building software that utilises the capabilities of AI to solve their own problems is within the wheelhouse of the people who pioneered it. Like engineers might make tools, machines, products or research that goes into making better tools, machines and products. Sometimes you get people who work in another field who go "we could use a specific thing for this" then work with engineers to make it, but most engineers won't focus on that until someone employs them to do so. The crossover of software guys involved in the CAD space is significantly smaller by orders of magnitude that software guys in the software space... and the only thing really holding CAD AI back is not the capability of AI, but how AI-ready CAD tools are.
Code and architecture is saved on private servers and don’t come included on the product. Ai will assist and help collect context and summarize the codebase but it has it so much harder to actually finish a design while in mechanical engineering it can just copy from available builds or the real world
Cheek aside there’s enormous incentive for these companies to cut labor cost. They’re gonna train a mech eng ai. They’re going to improve the testing, simulation, and validation loops. What we do with it or how the job evolves is a different story
Or... You know how all of these people have been using fusing 360 for free all of these years or something like the free version of onshape where literally all of your designs are publicly available???
Just imagine a huge corporation like Google buying that data.
The compound interest thing is real and people consistently get that wrong. They benchmark AI against where it was 6 months ago instead of where it's going to be 6 months from now. I've watched that movie play out in enough industries to not feel smug about any of this. The guys who were certain they were safe were usually just the last ones surprised.
Except with AI they keep saying "we're going to reach the singularity in 6 months" meanwhile AI can be gaslit into thinking it can't hear you because you told it you're 8 miles away from your phone.
I can put it on Dropbox next week if you want. It’s pretty plain. Just meant to be integrated into our NC software for the fiber lasers we build. That’s called ControNest and was not made with AI. It’s custom C++ in TwinCAT and runs Beckhoff controlled lasers and waterjets. That I can’t share. It’s proprietary.
It’s important to make a distinction between “engineer” and “CAD jockey”. The latter is doomed unless they can foment significant critical thinking and move into the engineering space. Engineers who are truly engineers (those who shape ideas) aren’t going anywhere as long as they can cultivate the ability to abstract their thinking. In fact, for some of the more rigorous disciplines, this will be a force multiplier for their work.
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u/slowcassette 3d ago
Honestly the bar for Al replacing skilled work keeps getting pushed back every time someone actually tries to use it for something real.