If You Aren’t Making Your Own Relays…

We’ve all been there. Someone will say something like, “I remember when we had to put our programs on a floppy disk…” Then someone will interrupt: “Floppy disk? We would have killed for floppy disks. We used paper tape…” After a few rounds, someone is talking about punching cards with a hand stylus or something. Next time someone is telling you about their relay computer, maybe ask them if they are buying their relays already built. They will almost surely say yes, and then you can refer them to [DiodeGoneWild], who shows how he is making his own relays.

While we don’t seriously suggest you make your own relays, there are a lot of fun techniques to pick up, from the abuse of a power drill to the calculation of the coil parameters. Even if you don’t learn anything, we get the desire to make as much as you can.

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Hackaday Prize 2023: Gen5X A Generatively Designed 5-Axis 3D Printer

[Ric Real] is entering the 2023 Hackaday Prize with the Gen5X, a generatively designed 3D printed five-axis 3D printer. The concept is not a new one, with the type of construction being seen a few times here and there. In addition to the usual three directions of motion, we’re familiar with, with the cartesian bot design, these types of machines add an additional two rotation axes, one which can swing the build platform front and back around the X-axis, and a second that provides rotation around the Z-axis. These combined motions give rise to some very interesting capabilities, outside of our familiar 3D printing design constraints.

As for the generative side of things, this is a largely theoretical idea. Essentially the concept is that the machine’s design can be iteratively updated and optimised for performance to fit into the constraints of available hardware such as motors and other ‘vitamins’ needed to create the next generation of machines. The design files should be parameterised enough such that this optimisation process can be automated, potentially via input from AI, but we suspect we’re a way off from that yet. Whether this project as yet satisfies any of these lofty goals remains to be seen, but do keep an eye on it if you’re so inclined. There is a Fusion 360 project here to dig into, but if you’re not interested in the research side of the project, but just want to build a 5-axis machine to play with, then you can find the project source on the GitHub Page.

If this feels familiar, you’d be on the right track, as we covered at least one other 5D printer recently. We have also touched upon generative design at least once. We’re sure we will see more on this topic in the future.

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Here’s Why GPUs Are Deep Learning’s Best Friend

If you have a curiosity about how fancy graphics cards actually work, and why they are so well-suited to AI-type applications, then take a few minutes to readĀ [Tim Dettmers] explain why this is so. It’s not a terribly long read, but while it does get technical there are also car analogies, so there’s something for everyone!

He starts off by saying that most people know that GPUs are scarily efficient at matrix multiplication and convolution, but what really makes them most useful is their ability to work with large amounts of memory very efficiently.

Essentially, a CPU is a latency-optimized device while GPUs are bandwidth-optimized devices. If a CPU is a race car, a GPU is a cargo truck. The main job in deep learning is to fetch and move cargo (memory, actually) around. Both devices can do this job, but in different ways. A race car moves quickly, but can’t carry much. A truck is slower, but far better at moving a lot at once. Continue reading “Here’s Why GPUs Are Deep Learning’s Best Friend”

Arduino-Powered Trap Hopes To Catch Mice

The old adage that you’ll make a fortune by developing a better mouse trap is not super realistic, as the engineers behind Sony’s Betamax video tape standard could tell you. However, you can still learn a lot building your own, as this project from [ROBO HUB] demonstrates.

The trap is intended to catch mice in a humane fashion, without injury to the animal. To that end, it uses an Arduino Nano armed with an ultrasonic distance sensorĀ  to detect when mice have entered a plastic container. The container’s hinged door is is held open with a servo. When a mouse is detected, the servo trips the door to snap shut under the power of an elastic band.

The key to making this design work well is ensuring that there are no gaps in the closed container that the mouse can use to escape. They’re wily creatures able to squeeze through positively tiny spaces, so it’s important to get this right. Besides that, you want to check the trap regularly, lest any caught mice simply claw and chew their way out.

We’ve seen a few mousetraps around these parts before, too. Video after the break.

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High Quality 3D Scene Generation From 2D Source, In Realtime

Here’s some fascinating work presented at SIGGRAPH 2023 of a method for radiance field rendering using a novel technique called Gaussian Splatting. What’s that mean? It means synthesizing a 3D scene from 2D images, in high quality and in real time, as the short animation shown above shows.

Neural Radiance Fields (NeRFs) are a method of leveraging machine learning to, in a way, do what photogrammetry does: synthesize complex scenes and views based on input images. But NeRFs work in a fraction of the time, and require only a fraction of the source material. There are different ways to go about this and unsurprisingly, there tends to be a clear speed vs. quality tradeoff. But as the video accompanying this new work seems to show, clever techniques mean the best of both worlds.

A short video summary is embedded just below the page break. Interested in deeper details? The research PDF is here. The amount of development this field has seen is nothing short of staggering, and certainly higher in quality than what was state-of-the-art for NeRFs only a year ago.

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Is A Pigeon Faster Than The Internet?

[Jeff Geerling]’s latest project is for the birds — literally. Even though he has a brand new high-speed fiber optic internet connection, online backups of YouTube video projects still take hours. He decided to see if the conclusions from a 2009 in South Africa study still hold true today — that using carrier pigeons to send files can be faster than the internet. [Jeff] sets up an experiment to send 3 TB of data by homing pigeon a distance of one mile to establish a baseline. Next, [Jeff] sends the same 3 TB of data over the internet, and donning the cap of honorary pigeon, simultaneously embarks on a journey by air to his off-site backup service in Nova Scotia, Canada.

Never underestimate the bandwidth of a station wagon full of tapes hurtling down the highway.

[Jeff] points out that you also have to consider the transfer time of your files onto and from the pigeon-suitable memory cards. He jumped through several hoops to minimize that, but it still consumed 2-1/2 hours total. Trying to keep the comparison fair, he also spent a couple days optimizing his internet connection to eek out the best possible speed. Continue reading “Is A Pigeon Faster Than The Internet?”

Solar Powered Flower Chases The Light

Many plants are capable of tracking the sun in order to get the most possible light. [hannu_hell] built a solar powered sculpture that replicates this light sensitivity for the benefit of better charging its own batteries, allowing it to run theoretically indefinitely where suitable light was available.

The 3D-printed flower features six movable petals mounted on an articulated stem. The flower’s leaves themselves bear solar panels that collect energy, analogous to leaves on a plant. A Raspberry Pi Pico is at the heart of the show, which is outfitted with a DS1307 real-time clock and a ST7735 TFT display for displaying date and time information. It’s also responsible for controlling servos that aim the flower’s solar panels towards the brightest light source available. This is achieved by using the Pico to read several photoresistors to determine light levels and adjust the leaves accordingly.

It’s a fun build, and one that could teach useful lessons relevant to even large-scale solar arrays. Video after the break.

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