Make Fancy Resin Printer 3D Models FDM-Friendly

March 19, 2025 by Donald Papp 17 Comments

Do you like high-detail 3D models intended for resin printing, but wish you could more easily print them on a filament-based FDM printer? Good news, because [Jacob] of Painted4Combat shared a tool he created to make 3D models meant for resin printers — the kind popular with tabletop gamers — easier to port to FDM. It comes in the form of a Blender add-on called Resin2FDM. Intrigued, but wary of your own lack of experience with Blender? No problem, because he also made a video that walks you through the whole thing step-by-step.

Resin2FDM separates the model from the support structure, then converts the support structure to be FDM-friendly.

3D models intended for resin printing aren’t actually any different, format-wise, from models intended for FDM printers. The differences all come down to the features of the model and how well the printer can execute them. Resin printing is very different from FDM, so printing a model on the “wrong” type of printer will often have disappointing results. Let’s look at why that is, to better understand what makes [Jacob]’s tool so useful.

Rafts and a forest of thin tree-like supports are common in resin printing. In the tabletop gaming scene, many models come pre-supported for convenience. A fair bit of work goes into optimizing the orientation of everything for best printed results, but the benefits don’t carry directly over to FDM.

For one thing, supports for resin prints are usually too small for an FDM printer to properly execute — they tend to be very thin and very tall, which is probably the least favorable shape for FDM printing. In addition, contact points where each support tapers down to a small point that connects to the model are especially troublesome; FDM slicer software will often simply consider those features too small to bother trying to print. Supports that work on a resin printer tend to be too small or too weak to be effective on FDM, even with a 0.2 mm nozzle.

To solve this, [Jacob]’s tool allows one to separate the model itself from the support structure. Once that is done, the tool further allows one to tweak the nest of supports, thickening them up just enough to successfully print on an FDM printer, while leaving the main model unchanged. The result is a support structure that prints well via FDM, allowing the model itself to come out nicely, with a minimum of alterations to the original.

Resin2FDM is available in two versions, the Lite version is free and an advanced version with more features is available to [Jacob]’s Patreon subscribers. The video (embedded below) covers everything from installation to use, and includes some general tips for best results. Check it out if you’re interested in how [Jacob] solved this problem, and keep it in mind for the next time you run across a pre-supported model intended for resin printing that you wish you could print with FDM.

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How To Use LLMs For Programming Tasks

March 11, 2025 by Donald Papp 58 Comments

[Simon Willison] has put together a list of how, exactly, one goes about using a large language models (LLM) to help write code. If you have wondered just what the workflow and techniques look like, give it a read. It’s full of examples, strategies, and useful tips for effectively using AI assistants like ChatGPT, Claude, and others to do useful programming work.

It’s a very practical document, with [Simon] emphasizing realistic expectations and the importance of managing context (both in terms of giving the LLM direction, as well as the model’s context in terms of being mindful of how much the LLM can fit in its ‘head’ at once.) It is useful to picture an LLM as a capable and obedient but over-confident programming intern or assistant, albeit one that never gets bored or annoyed. Useful work can be done, but testing is crucial and human oversight simply cannot be automated away.

Even if one has no interest in using LLMs to help in writing production code, there’s still a lot of useful work they can do to speed up the process of software development in general, especially when learning. They can help research options, interactively explore unfamiliar codebases, or prototype ideas quickly. [Simon] provides useful strategies for all these, and more.

If you have wondered how exactly glorified chatbots can meaningfully help with software development, [Simon]’s writeup hopefully gives you some new ideas. And if this is is all leaving you curious about how exactly LLMs work, in the time it takes to enjoy a warm coffee you can learn how they do what they do, no math required.

Josephine Cochrane Invented The Modern Dishwasher — In 1886

March 11, 2025 by Donald Papp 42 Comments

Popular Science has an excellent article on how Josephine Cochrane transformed how dishes are cleaned by inventing an automated dish washing machine and obtaining a patent in 1886. Dishwashers had been attempted before, but hers was the first with the revolutionary idea of using water pressure to clean dishes placed in wire racks, rather than relying on some sort of physical scrubber. The very first KitchenAid household dishwashers were based on her machines, making modern dishwashers direct descendants of her original design.

It wasn’t an overnight success. Josephine faced many hurdles. Saying it was difficult for a woman to start a venture or do business during this period of history doesn’t do justice to just how many barriers existed, even discounting the fact that her late husband was something we would today recognize as a violent alcoholic. One who left her little money and many debts upon his death, to boot.

She was nevertheless able to focus on developing her machine, and eventually hired mechanic George Butters to help create a prototype. The two of them working in near secrecy because a man being seen regularly visiting her home was simply asking for trouble. Then there were all the challenges of launching a product in a business world that had little place for a woman. One can sense the weight of it all in a quote from Josephine (shared in a write-up by the USPTO) in which she says “If I knew all I know today when I began to put the dishwasher on the market, I never would have had the courage to start.”

But Josephine persevered and her invention made a stir at the 1893 World’s Fair in Chicago, winning an award and mesmerizing onlookers. Not only was it invented by a woman, but her dishwashers were used by restaurants on-site to clean tens of thousands of dishes, day in and day out. Her marvelous machine was not yet a household device, but restaurants, hotels, colleges, and hospitals all saw the benefits and lined up to place orders.

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The Pentium Processor’s Innovative (and Complicated) Method Of Multiplying By Three, Fast

March 8, 2025 by Donald Papp 26 Comments

[Ken Shirriff] has been sharing a really low-level look at Intel’s Pentium (1993) processor. The Pentium’s architecture was highly innovative in many ways, and one of [Ken]’s most recent discoveries is that it contains a complex circuit — containing around 9,000 transistors — whose sole purpose is to multiply specifically by three. Why does such an apparently simple operation require such a complex circuit? And why this particular operation, and not something else?

Let’s back up a little to put this all into context. One of the feathers in the Pentium’s cap was its Floating Point Unit (FPU) which was capable of much faster floating point operations than any of its predecessors. [Ken] dove into reverse-engineering the FPU earlier this year and a close-up look at the Pentium’s silicon die shows that the FPU occupies a significant chunk of it. Of the FPU, nearly half is dedicated to performing multiplications and a comparatively small but quite significant section of that is specifically for multiplying a number by three. [Ken] calls it the x3 circuit.

The “x3 circuit”, a nontrivial portion of the Pentium processor, is dedicated to multiplying a number by exactly three and contains more transistors than an entire Z80 microprocessor.

Why does the multiplier section of the FPU in the Pentium processor have such specialized (and complex) functionality for such an apparently simple operation? It comes down to how the Pentium multiplies numbers.

Multiplying two 64-bit numbers is done in base-8 (octal), which ultimately requires fewer operations than doing so in base-2 (binary). Instead of handling each bit separately (as in binary multiplication), three bits of the multiplier get handled at a time, requiring fewer shifts and additions overall. But the downside is that multiplying by three must be handled as a special case.

[Ken] gives an excellent explanation of exactly how all that works (which is also an explanation of the radix-8 Booth’s algorithm) but it boils down to this: there are numerous shortcuts for multiplying numbers (multiplying by two is the same as shifting left by 1 bit, for example) but multiplying by three is the only one that doesn’t have a tidy shortcut. In addition, because the result of multiplying by three is involved in numerous other shortcuts (x5 is really x8 minus x3 for example) it must also be done very quickly to avoid dragging down those other operations. Straightforward binary multiplication is too slow. Hence the reason for giving it so much dedicated attention.

[Ken] goes into considerable detail on how exactly this is done, and it involves carry lookaheads as a key element to saving time. He also points out that this specific piece of functionality used more transistors than an entire Z80 microprocessor. And if that is not a wild enough idea for you, then how about the fact that the Z80 has a new OS available?

The Road To Lucid Dreaming Might Be Paved With VR

March 7, 2025 by Donald Papp 26 Comments

Lucid dreaming is the state of becoming aware one is dreaming while still being within the dream. To what end? That awareness may allow one to influence the dream itself, and the possibilities of that are obvious and compelling enough that plenty of clever and curious people have formed some sort of interest in this direction. Now there are some indications that VR might be a useful tool in helping people achieve lucid dreaming.

The research paper (Virtual reality training of lucid dreaming) is far from laying out a conclusive roadmap, but there’s enough there to make the case that VR is at least worth a look as a serious tool in the quest for lucid dreaming.

One method of using VR in this way hinges on the idea that engaging in immersive VR content can create mild dissociative experiences, and this can help guide and encourage users to perform “reality checks”. VR can help such reality checks become second nature (or at least more familiar and natural), which may help one to become aware of a dream state when it occurs.

Another method uses VR as a way to induce a mental state that is more conducive to lucid dreaming. As mentioned, engaging in immersive VR can induce mild dissociative experiences, so VR slowly guides one into a more receptive state before falling asleep. Since sleeping in VR is absolutely a thing, perhaps an enterprising hacker with a healthy curiosity in lucid dreaming might be inspired to experiment with combining them.

We’ve covered plenty of lucid dreaming hacks over the years and there’s even been serious effort at enabling communication from within a dreaming state. If you ask us, that’s something just begging to be combined with VR.

A Precisely Elegant Cyberdeck Handheld

February 27, 2025 by Donald Papp 15 Comments

[Nicholas LaBonte] shows off a Cyberdeck Handheld that demonstrates just how good something can look when care and attention goes into the design and fabrication. He wanted to make something that blended cyberpunk and nautical aesthetics with a compact and elegant design, and we think he absolutely succeeded.

On the inside is a Raspberry Pi and an RTL-SDR. The back of the unit is machined from hardwood, and sports a bronze heat sink for the Raspberry Pi. The front has a prominent red PSP joystick for mouse input and a custom keyboard. The keyboard is especially interesting. On the inside it’s a custom PCB with tactile switches and a ATmega32U4 running QMK firmware — a popular choice for DIY keyboards — and presents to the host as a regular USB HID device.

The keys are on a single plate of little tabs, one for each key, that sits between the front panel and press on the tact switches inside.

How did he make those slick-looking keys? It’s actually a single plate that sits between the front panel and the switches themselves. [Nicholas] used a sheet of polymer with a faux-aluminum look to it and machined it down, leaving metal-looking keys with engraved symbols as tabs in a single panel. It looks really good, although [Nicholas] already has some ideas about improving it.

On the right side is the power button and charging port, and astute readers may spot that the power button is where a double-stack of USB ports would normally be on a Raspberry Pi 5. [Nicholas] removed the physical connectors, saving some space and connecting the USB ports internally to the keyboard and SDR.

As mentioned, [Nicholas] is already full of ideas for improvements. The bronze heat sink isn’t as effective as he’d like, the SDR could use some extra shielding, and the sounds the keyboard ends up making could use some work. Believe it or not, there’s still room to spare inside the unit and he’d maybe like to figure out a way to add a camera, GPS receiver, or maybe a 4G modem. We can’t wait! Get a good look for yourself in the video, embedded below.

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New Camera Does Realtime Holographic Capture, No Coherent Light Required

February 26, 2025 by Donald Papp 31 Comments

Holography is about capturing 3D data from a scene, and being able to reconstruct that scene — preferably in high fidelity. Holography is not a new idea, but engaging in it is not exactly a point-and-shoot affair. One needs coherent light for a start, and it generally only gets touchier from there. But now researchers describe a new kind of holographic camera that can capture a scene better and faster than ever. How much better? The camera goes from scene capture to reconstructed output in under 30 milliseconds, and does it using plain old incoherent light.

The camera and liquid lens is tiny. Together with the computation back end, they can make a holographic capture of a scene in under 30 milliseconds.

The new camera is a two-part affair: acquisition, and calculation. Acquisition consists of a camera with a custom electrically-driven liquid lens design that captures a focal stack of a scene within 15 ms. The back end is a deep learning neural network system (FS-Net) which accepts the camera data and computes a high-fidelity RGB hologram of the scene in about 13 ms. How good are the results? They beat other methods, and reconstruction of the scene using the data looks really, really good.

One might wonder what makes this different from, say, a 3D scene captured by a stereoscopic camera, or with an RGB depth camera (like the now-discontinued Intel RealSense). Those methods capture 2D imagery from a single perspective, combined with depth data to give an understanding of a scene’s physical layout.

Holography by contrast captures a scene’s wavefront information, which is to say it captures not just where light is coming from, but how it bends and interferes. This information can be used to optically reconstruct a scene in a way data from other sources cannot; for example allowing one to shift perspective and focus.

Being able to capture holographic data in such a way significantly lowers the bar for development and experimentation in holography — something that’s traditionally been tricky to pull off for the home gamer.