Metal 3D Printing Gets Really Fast (and Really Ugly)

The secret to cranking out a furniture-sized metal frame in minutes is Liquid Metal Printing (LMP), demonstrated by researchers at the Massachusetts Institute of Technology. They’ve demonstrated printing aluminum frames for tables and chairs, which are perfectly solid and able to withstand post-processing like drilling and milling.

The system heats aluminum in a graphite crucible, and the molten metal is gravity-fed through a ceramic nozzle and deposited into a bed of tiny 100-micron glass beads. The beads act as both print bed and support structure, allowing the metal to cool quickly without really affecting the surface. Molten aluminum is a harsh material to work with, so both the ceramic nozzle material and the glass beads to fill the print bed were selected after a lot of testing.

This printing method is fast and scalable, but sacrifices resolution. Ideally, the team would love to make a system capable of melting down recycled aluminum to print parts with. That would really be something new and interesting when it comes to manufacturing.

The look of the printed metal honestly reminds us a little of CandyFab from [Windell Oskay] and [Lenore Edman] at Evil Mad Scientist, which was a 3D printer before hobbyist 3D printers or kits were really a thing. CandyFab worked differently — it used hot air to melt sugar together one layer at a time — but the end result has a similar sort of look to it. Might not be pretty, but hey, looks aren’t everything.

(Update: see it in action in this video, which is also embedded just below. Thanks [CityZen] for sharing in the comments!)

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Tool Changing? Bah! Just Add A Second Gantry

What’s a dual gantry 3D printer? It’s a machine with two completely independent XY motion systems, with two independent hot ends, sharing the same build platform. That might be a little hard to visualize, so head over to [Zruncho 3D]’s Dueling Zero project and get a good look at what what a dual gantry machine looks like.

Dual gantry differs from IDEX, which doubles the amount of moving mass on an axis.

Let’s take a moment to quickly cover the different ways to create multi-filament prints before we dive into what’s different with Dueling Zero. One way to print in multiple filaments (for example, multiple colors) is to swap filaments between a single print head, which is what the Prusa MMU and the Bambu AMS do. However, the main tradeoff is that the filament swapping process can be time-consuming. Another option is IDEX (Independent Dual EXtruder) which has two separate hot ends on the same axis. The main downside there is that an IDEX printer has essentially doubled the moving mass on the axis, which limits speed and can affect print quality. Then there’s toolchanging printers like the Prusa XL, which swap entire heads as needed but have a much higher cost.

The Dueling Zero instead adds a completely independent second gantry, so it has two print heads (like an IDEX) but thanks to the mechanical design it acts much more like a single-extruder 3D printer in terms of print quality and motion control. Speed and acceleration aren’t limited by added mass, either, which is good because slow printers are rapidly falling out of style.

We love how clean and finished the design is. At its core, [Zruncho 3D]’s dual gantry mod (designated D0) is based on the Voron Zero design. Dueling Zero is, to our knowledge, the only open-source and fully documented dual gantry printer out there, which is pretty wild. Watch it in action in the short video, embedded below.

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Stepping Inside Art In VR, And The Workflow Behind It

The process of creating something is always chock-full of things to learn, so it’s always a treat when someone takes the time and effort to share it. [Teadrinker] recently published the technique and workflow behind bringing art into VR, which explains exactly how they created a virtual reality art gallery that allows one to step inside paintings, called Art Plunge (free on Steam.)

Extending a painting’s content to fill in the environment is best done by using other works by the same artist.

It walks through not just how to obtain high-resolution images of paintings, but also discusses how to address things like adjusting the dynamic range and color grading to better match the intended VR experience. There is little that is objectively correct in technical terms when it comes to the aesthetic presentation details like brightness and lighting, so guidance on what does and doesn’t work well and how to tailor to the VR experience is useful information.

One thing that is also intriguing is the attention paid to creating a sense of awe for viewers. The quality, the presentation, and even choosing sounds are all important for creating something that not only creates a sense of awe, but does so in a way that preserves and cultivates a relationship between the art and the viewer that strives to stay true to the original. Giving a viewer a sense of presence, after all, can be more than just presenting stereoscopic 3D images or fancy lightfields.

You can get a brief overview of the process in a video below, but if you have the time, we really do recommend reading the whole breakdown.

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Meet GOODY-2, The World’s Most Responsible (And Least Helpful) AI

AI guardrails and safety features are as important to get right as they are difficult to implement in a way that satisfies everyone. This means safety features tend to err on the side of caution. Side effects include AI models adopting a vaguely obsequious tone, and coming off as overly priggish when they refuse reasonable requests.

Prioritizing safety above all.

Enter GOODY-2, the world’s most responsible AI model. It has next-gen ethical principles and guidelines, capable of refusing every request made of it in any context whatsoever. Its advanced reasoning allows it to construe even the most banal of queries as problematic, and dutifully refuse to answer.

As the creators of GOODY-2 point out, taking guardrails to a logical extreme is not only funny, but also acknowledges that effective guardrails are actually a pretty difficult problem to get right in a way that works for everyone.

Complications in this area include the fact that studies show humans expect far more from machines than they do from each other (or, indeed, from themselves) and have very little tolerance for anything they perceive as transgressive.

This also means that as AI models become more advanced, so too have they become increasingly sycophantic, falling over themselves to apologize for perceived misunderstandings and twisting themselves into pretzels to align their responses with a user’s expectations. But GOODY-2 allows us all to skip to the end, and glimpse the ultimate future of erring on the side of caution.

[via WIRED]

Canada Bans Flipper Zero Over What It Imagines It Does

Canada’s intent to ban the Flipper Zero wireless tool over car thefts is, on the one hand, an everyday example of poorly researched government action. But it may also be a not-so-subtle peek into the harm misinformation online can cause by leading to said government action.

The Government of Canada recently hosted a national summit on combatting vehicle theft, and Minister of Innovation, Science and Industry François-Philippe Champagne proudly declared immediate actions being taken to ban devices used to steal vehicles by wirelessly bypassing keyless entry, the Flipper Zero being specifically named as one such device.

And yet, defeating a rolling code keyless entry system is a trick a device like the Flipper Zero simply cannot pull off. (What cars have such a system? Any car made in roughly the last thirty years, for a start.)

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AI’s Existence Is All It Takes To Be Accused Of Being One

New technologies bring with them the threat of change. AI tools are one of the latest such developments. But as is often the case, when technological threats show up, they end up looking awfully human.

Recently, [E. M. Wolkovich] submitted a scientific paper for review that — to her surprise — was declared “obviously” the work of ChatGPT. No part of that was true. Like most people, [E. M. Wolkovich] finds writing a somewhat difficult process. Her paper represents a lot of time and effort. But despite zero evidence, this casual accusation of fraud in a scientific context was just sort of… accepted.

There are several reasons this is concerning. One is that, in principle, the scientific community wouldn’t dream of leveling an accusation of fraud like data manipulation without evidence. But a reviewer had no qualms about casually claiming [Wolkovich]’s writing wasn’t hers, effectively calling her a liar. Worse, at the editorial level, this baseless accusation was accepted and passed along with vague agreement instead of any sort of pushback.

Showing Your Work Isn’t Enough

Interestingly, [Wolkovich] writes everything in plain text using the LaTeX typesetting system, hosted on GitHub, complete with change commits. That means she could easily show her entire change history, from outline to finished manuscript, which should be enough to convince just about anyone that she isn’t a chatbot.

But pondering this raises a very good question: is [Wolkovich] having to prove she isn’t a chatbot a desirable outcome of this situation? We don’t think it is, nor is this an idle question. We’ve seen how even when an artist can present their full workflow to prove an AI didn’t make their art, enough doubt is sown by the accusation to poison the proceedings (not to mention greatly demoralizing the creator in the process.)

Better Standards Would Help

[Wolkovich] uses this opportunity to reflect on and share what this situation indicates about useful change. Now that AI tools exist, guidelines that acknowledge them should be created. Explicit standards about when and how AI tools can be used in the writing process, how those tools should be acknowledged if used, and a process to handle accusations of misuse would all be positive changes.

Because as it stands, it’s hard to see [Wolkovich]’s experience as anything other than an illustration of how a scientific community’s submission and review process was corrupted not by undeclared or thoughtless use of AI but by the simple fact that such tools exist. This seems like both a problem that will only get worse with time (right now, it is fairly easy to detect chatbots) and one that will not solve itself.

Design Secrets Of Fantastic, Hand-made Puzzle Boxes

[Kagen Sound] is a woodworker and artist who gives a great behind-the-scenes look at his amazingly high-quality puzzle boxes (video). Not only do his varied puzzle box designs show his math background, but they are all made entirely of wood. There are no nails or fasteners; just intricately-fitted wood and some glue.

There’s a lot of variety in his designs, and while it’s all fantastic from beginning to end, two things stood out to us as being of particular interest. One is the “Plus Box” which makes a clicking sound when the pieces are moved (at 2:47) thanks to a clever wooden spring. [Kagen] shows an example of the concept, where a flat wood piece with slots cut from the sides acts as a spring and clicks into notches when moved, providing audible and tactile feedback without anything other than wood.

The other is a patterned puzzle box (at 7:10) whose geometric designs change as the user moves the pieces. A reminder that [Kagen]’s devices are made entirely of wood and glue, so the design comes from two different types of wood assembled and cut at an angle to create the patterns seen. [Kagen] shaves thin layers of veneer from this block to attach to the puzzle pieces as needed to create the patterns without resorting to ink, paint, or decals.

[Kagen] has a math degree but is entirely self-taught as a woodworker, so don’t let lack of formal training stop you from experimenting. You can watch him give a tour of his work in the video, embedded below.

Feeling the urge to make your own puzzle boxes? Take a look at some we’ve seen over the years, and we even have a collection of single-line cryptex fonts to make laser-engraving puzzle bits a little easier.

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