This $4 Desalination Device Provides Drinking Water For The Whole Family

Researchers at MIT and in China have improved the old-fashioned solar still with a new inexpensive device that harnesses the sun to remove salt from water. Traditionally, these kinds of systems use a wick to draw water, but once the wick becomes fouled with salt, the device needs cleaning or other maintenance. Not exactly what you want in a survival situation. You can read the paper in Nature if you want more details.

The key to this new technique is black paint and polyurethane with 2.5-millimeter holes drilled in it. The idea is that warmer water above the insulating medium causes the salt to concentrate in the cooler water beneath the insulator allowing efficient vaporization of the water.  As the water evaporates, it causes the salt concentration at the top to rise, which then sinks due to the higher density and lower-concentration salt water rises to the top to evaporate.

Because the materials are commonplace, the team says a one-meter-square system costs about $4 to produce. A system that size could provide a family’s daily drinking water.

So far, the prototype system has worked in the lab for at least a week without accumulating salt. The next challenge is to scale it to something more practical, but due to the low cost and simplicity of the system, it seems it would be easy enough to make that happen or to reproduce the device for your own testing.

Desalination is a problem you can approach from many different angles. You can also harvest clean water from fog, something else that started at MIT.

Bug Eliminator Zaps With A Laser

Mosquitoes tend to be seen as an almost universal negative, at least in the lives of humans. While they serve as a food source for plenty of other animals and may even pollinate some plants, they also carry diseases like malaria and Zika, not to mention the itchy bites. Various mosquito deterrents have been invented over the years to solve some of these problems, but one of the more interesting ones is this project by [Ildaron] which attempts to build a mosquito-tracking laser.

The device uses a neural learning algorithm to identify mosquitoes flying nearby. Once a mosquito is detected, a laser is aimed at it and activated in order to “thermally neutralize” the pest. The control system as well as the neural network and machine learning are hosted on a Raspberry Pi and Jetson Nano which give it plenty of computing power. The only major downside with this specific project is that the high-powered laser can be harmful to humans as well.

Ideally, a market for devices like these would bring the price down, perhaps even through the use of something like an ASIC specifically developed for these mosquito-targeting machines. In the meantime, [Ildaron] has made this project available for replication on his GitHub page. We have also seen similar builds before which are effective against non-flying insects, so it seems like only a matter of time before there is more widespread adoption — either that or Judgement day!

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The SoM on an evaluation board, with two LEDs shining, one USB-C cable connected for power and another plugged into the OTG port

New Part Day: X1501 Makes For A Tiny And Open Linux SoM

Ever wanted to run Linux in an exceptionally small footprint? Then [Reimu NotMoe] from [SudoMaker] has something for you! She’s found an unbelievably small Linux-able chip in BGA, and designed a self-contained tiny SoM (System on Module) breakout with power management and castellated pads. This breakout contains everything you need to have Linux in a 16x16x2mm footprint. For the reference, a 16mm square is the size of the CPU on a Raspberry Pi.

This board isn’t just tiny, it’s also well-thought-out, helping you put the BGA-packaged Ingenic X1501 anywhere with minimal effort. With castellated pads, it’s easy to hand-solder this SoM for development and reflow for production. An onboard switching regulator works from 6V down to as low as 3V, making this a viable battery-powered Linux option. It can even give you up to 3.3V/1A for all your external devices.

The coolest part yet – the X1501 is surprisingly friendly and NDA-free. The datasheets are up for grabs, there are no “CONFIDENTIAL” watermarks – you get a proper 730-page PDF. Thanks to this openness, the X1501 can run mainline Linux with minimal changes, with most of the peripherals already supported. Plus, there’s Efuse-based Secure Boot if your software needs to be protected from cloning.

More after the break…

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Quantum Computing: The First Taste Is Free

There are a few ways to access real quantum computers — often for free — over the Internet. However, most of these are previous-generation machines that have limited capabilities. Great for learning, perhaps, but not something you could do anything practical with.  Xanadu, however, has announced what they claim to be a computer capable of reaching quantum advantage that is free for anyone to use, within limits. Borealis — the computer in question — uses photonic states and has the capability of working with over 216 squeezed-state qubits.

The company is selling time on the computer, but the free tier includes 5 million free shots on Borealis and 10 million shots on an earlier series of quantum computers. You can also buy pay-as-you go service for about $100 per million shots on Borealis.

While a few million shots may sound like a lot, we noticed that the quickstart demo consumes 10,000 shots and that’s presumably something simple. That’s still about 500 runs of that on Borealis — not bad for free on a state-of-the-art quantum computer. You will be wanting to debug with a simulator, though.

We presume the developers are Beatles fans given that you use software called Penny Lane and Strawberry Fields to access the machines. Your job is controlled by Python and there is a cloud simulator to save your shots.

We won’t pretend to understand all there is about squeezed light qubits and the Borealis architecture. But you can get some general practice in our series on quantum computing. Or there are a few lectures around including one that aims at different levels of experience.

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Hackaday Links: June 5, 2022

The big news this week comes from the world of medicine, where a woman has received a 3D-printed ear transplant. The 20-year-old woman suffered from microtia, a rare congenital deformity that left her without a pinna, the external structure of the ear. Using scans of the normal ear, doctors were able to make a 3D model of what the missing pinna should look like. Raw material for the print was taken from the vestigial ear of the patient in the form of cartilage cells, or chondrocytes. The ear was printed using a bioprinter, which is a bit like an inkjet printer. The newly printed ear was placed into a protective structure and transplanted. The operation was done in March, and the results are pretty dramatic. With a little squinting, it does look a bit like there are some printing artifacts in the ear, but we’d imagine that’s more from the protective cage that was over the ear as it healed.

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A light blue marker with a two-pin header replacing the tip, being pressed against the back of the keypad baord that's removed from the safe

Anyone Can Be The Master Of This Master Lock Safe

[Etienne Sellan] got one of these lovely $5 logic analyzers. As with any shiny new tool, he started looking for things to investigate with it, and his gaze fell on a Sentry Safe (produced by Master Lock). On the surface level, this keypad-equipped safe is designed decently when it comes to privilege separation. You can take the keypad board off and access its backside, but the keypad doesn’t make any decisions, it merely sends the digits to a different board embedded behind the safe’s door. The solenoid-connected board receives the PIN, verifies it, and then controls the solenoid that unlocks the safe.

[Etienne] hooked up a logic analyzer to the communication wire, which turned out to be a UART channel, and logged the keypad communication packets — both for password entry and for password change. Then, he wrote some Arduino code to send the same packets manually, which worked wonders. Bruteforcing wasn’t viable, however, due to rate limitation in the solenoid controller. Something drew his attention from there – if you want to change the password, the keypad requires you enter the factory code, unique to each safe and supplied in the instruction manual. That code entry is a separate kind of packet from the “change password” one.

More after the break…

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The Ethics Of When Machine Learning Gets Weird: Deadbots

Everyone knows what a chatbot is, but how about a deadbot? A deadbot is a chatbot whose training data — that which shapes how and what it communicates — is data based on a deceased person. Now let’s consider the case of a fellow named Joshua Barbeau, who created a chatbot to simulate conversation with his deceased fiancee. Add to this the fact that OpenAI, providers of the GPT-3 API that ultimately powered the project, had a problem with this as their terms explicitly forbid use of their API for (among other things) “amorous” purposes.

[Sara Suárez-Gonzalo], a postdoctoral researcher, observed that this story’s facts were getting covered well enough, but nobody was looking at it from any other perspective. We all certainly have ideas about what flavor of right or wrong saturates the different elements of the case, but can we explain exactly why it would be either good or bad to develop a deadbot?

That’s precisely what [Sara] set out to do. Her writeup is a fascinating and nuanced read that provides concrete guidance on the topic. Is harm possible? How does consent figure into something like this? Who takes responsibility for bad outcomes? If you’re at all interested in these kinds of questions, take the time to check out her article.

[Sara] makes the case that creating a deadbot could be done ethically, under certain conditions. Briefly, key points are that a mimicked person and the one developing and interacting with it should have given their consent, complete with as detailed a description as possible about the scope, design, and intended uses of the system. (Such a statement is important because machine learning in general changes rapidly. What if the system or capabilities someday no longer resemble what one originally imagined?) Responsibility for any potential negative outcomes should be shared by those who develop, and those who profit from it.

[Sara] points out that this case is a perfect example of why the ethics of machine learning really do matter, and without attention being paid to such things, we can expect awkward problems to continue to crop up.