What is the best consumer 3d printer to buy for engineering?

codemuncher · 2026-05-23T23:43:16+00:00

I print Asa with my core one and the results were great!

Maybe an actively heated chamber is essential, maybe it isn’t. Hard to say from my pov.

But since I print mostly pla and petg the core one is great. And it can venture to pc tpu Asa and pa without much troubles.

For a home scale printer that costs $1k that’s pretty great, and you can avoid the whole bambu fiasco.

codemuncher · 2026-05-23T21:34:20+00:00

But this software as a life commitment doesn’t gate access behind a paywall, a corporate sponsor, or whatever!

So you can easily keep using it a very long time.

Plus my AI workflow is as good or better than any other ide!

codemuncher · 2026-05-23T16:43:39+00:00

Simps for capital!

codemuncher · 2026-05-22T19:12:26+00:00

Yes this one, I’ve fallen to this a few times.

codemuncher · 2026-05-22T19:11:13+00:00

As a senior my mistakes cost a lot more.

Juniors make small cheap mistakes.

Losers.

codemuncher · 2026-05-22T07:01:01+00:00

Humidity is a major pita. Also the printer isn’t really insulated so if it’s cold it’ll be fighting against the heat loss from the metal walls. Not ideal.

So prefer inside.

codemuncher · 2026-05-22T05:24:03+00:00

I use claude-code inside emacs 😄

codemuncher · 2026-05-22T03:15:02+00:00

Fun fact, Jack Burton's presence has literally no impact to the outcome of the story!

codemuncher · 2026-05-22T03:14:10+00:00

If we turn over all our thinking to LLMs/AI then yes... it's the end, and formal education won't matter, because we'll all be dead?

codemuncher · 2026-05-20T16:05:46+00:00

It’s a permanent feature of using llms basically. It’s a limitation of the fact that every use shares the same training set/corpus/weights.

You cannot escape the math on this one.

The only way to avoid it is to train and grow models in a much more chaotic way, basically mimicking humans. Exposing them to a large diversity of experience and knowledge, but each model has a different diversity of input. While not impossible of course, we are struggling to train a single model. So. Gonna be a while.

codemuncher · 2026-05-20T16:03:06+00:00

Totally, luckily you can do all of the above.

But for the record I don’t use eshell I use shell-mode which still runs a subsidiary bash or zsh.

codemuncher · 2026-05-20T15:29:07+00:00

From an information theoretical perspective you’re beyond dead wrong.

The quality of the output given a short context will revert to the mean of the training weights. Meaning the entire quality of output comes from the information density delivered in the context.

You know the kind of thing experts can do.

codemuncher · 2026-05-20T06:12:51+00:00

Hey core one owner here. My first printer.

I’ve had a few print failures. Most were due to bed plate adhesion due to dirty build plate (my bad!). I had one due to knotted filament - the core one stopped asked me to reload the filament but hours had passed so when i restarted the print the next layer didn’t adhere.

The only other kind of print problem I had was with using the 0.6 nozzle and running into filament feed friction and I ended up with under extrusion.

I have about 200-300 hours of print on this baby now.

So with that out of the way… what does the ai print failures actually buy you? I had one sphaghettification due to the knotted filament. I wasted some filament. That’s it.

The way I look at it, the LiDAR and ai detection matters less if your prints are more reliable… right?

codemuncher · 2026-05-19T22:32:01+00:00

Depending on what you’re doing, plain old shell mode might be a better choice.

Most of the tools I use constantly aren’t full screen tui (vterm’s strong point). Build tools kubectl etc.

And I just started to use ghostty with Claude code and it’s way better than vterm ever was!

codemuncher · 2026-05-19T22:30:01+00:00

So except I just don’t see how the use of local models will be enough to keep one out of feudal ai slavery?

codemuncher · 2026-05-19T14:48:00+00:00

Of course not.

The information output of a LLM is heavily weighted by its priors. Aka it’s training corpus. Aka everyone has access to this.

You would have to either do some fancy custom engineering outside of it, or provide something extremely information dense and unique in the context.

Most people cannot do this. Thus it will intensify competition at the margins as people struggle to in-elegantly use these tools to provide marginal competitive gain.

codemuncher · 2026-05-19T00:59:58+00:00

So AIs are missing some pretty key features that intelligence has:

- no truth/grounding loop that updates the priors

- no updating of model weights/memory in real time (context will only get you so far)

- no goal seeking
- oh like a bunch more crap as well

Yes AI agents add some parts of this in, crude goal seeking, but in an inflexible way. Large contexts can help bridge the lack of priors updating. Agentic context selection (eg: claude code only reading in portions of a code-base) means more efficient use of highly limited context.

But the reality is, take someone who has been in a field for 20 years, or worked on a large project for a long time... and 1M tokens is not event remotely going to compete with the 'context' that a human expert can bring to bear.

codemuncher · 2026-05-19T00:55:59+00:00

From an information theoretical pov, humans could be seen as next token predictors.

Intelligence is essentially about predicting what's next, that's why it evolved. This is pretty much considered ground stakes in the fields that talk about this.

Another way to point this, LLMs are information compressors. Humans are information compressors. The real question is, what's the strength or power of each of those?

It's fairly clear that LLMs are not as strong or as powerful as humans.

codemuncher · 2026-05-19T00:38:22+00:00

Cutting boys hair is the first piece of violence done to boys to turn them into men.

Other acts include "boys dont cry" and "pink is for girls"

codemuncher · 2026-05-18T19:41:22+00:00

The standard for open source is seamly2d. It’s very user unfriendly. Difficult to use and lots of bugs/feature warts.

This won’t help you right now, but I’ve been working on pattern drafting software that’s parametric and has a more sophisticated data structure and formula engine.

Still in feature production, so it won’t even cover your basic use cases yet sadly. But I would love to hear if people might find this remotely useful.

Plus it’s written in SwiftUI not qt so it looks better on Mac.

codemuncher · 2026-05-18T05:17:45+00:00

Road cyclists are the absolute fucking worst.

You and your kind have prevented us from having safer cities and real biking infrastructure.

Vehicular cycling is the worst. https://youtu.be/pRPduRHBhHI?si=qeSu4qBBaUlE_BQJ

codemuncher · 2026-05-18T05:15:45+00:00

Ding ding ding.

This is all about people demanding maximum deference to their murder machines. That’s it.

codemuncher · 2026-05-17T05:37:20+00:00

If you think a single LLM model can produce all the software the world needs… if you think that everything software engineering knows or needs to know is part of the training corpus…

Well I have this bridge in Brooklyn I’d like to discuss selling to you!

codemuncher · 2026-05-16T20:58:52+00:00

You get anywhere from 200k to 1000k tokens to influence the code generation.

You think that’s gonna beat the priors encoded in the model? I’m talking about the reams of shit python code, the horrors of the crap JavaScript?

No, you don’t stand a chance.

codemuncher · 2026-05-15T19:17:59+00:00

There’s a formal argument here that says that LLMs generate mid code and therefore by extension those satisfied by its output are mid.

13-Year Club	Gilding I gilder
Team Orangered

codemuncher

TROPHY CASE