Mysterious Files PH

Oh sure, you’ve got calculators. There’s that phone program of course, and the one that comes with your OS, and the TI-86 and possibly RPN numbers you’ve had since high school.

But what you don’t have is a Flapulator, at least not until you build one. Possibly the be-all, end-all of physical calculating devices, the Flapulator does its calculating live on a split-flap display. It’s kind of slow and the accuracy is questionable, but the tactility is oh, so good.

This baby boasts a 6-digit display, where the decimal point and negative sign each require one digit. Inside is a Raspberry Pi Pico, which can calculate for around 4 hours on a full charge. But the coolest part (aside from the split-flap display, naturally) has got to be the 24-key, hand-wired mechanical keyboard. There’s also a couple of LEDs that light up to keep track of the current mathematical operation.

The story behind this one is kind of interesting. [Applepie1928] found out that one of their favorite mathematician-comedian-pi-lovers who is known for signing calculators was coming to town. With four weeks to whip something up, this was, amazingly, the result. Check it out in  action after the break.

Need something that’s a whole other kind of fancy? Here’s an open-source graphing calculator.

From laser cutters to 3D printers, having an exhaust duct at the back of a machine is a very common sight. However, these tend to be rather bulky, claiming many centimeters of precious space behind a machine even if you’d want to push it right up against a wall. This issue annoyed [TheNeedleStacker] over on YouTube so much that he had a poke at solving this problem with angled exhaust ducts, all hopefully without impairing its basic function.

Although there are some online offerings for angled exhaust port extenders, these do not quite fit the required 6″ diameter. Reducing the problem to just a matter of cross section area for simplicity’s sake, that means a 19″ wide duct at a depth of 1.5″. Making sure the transition from the tube to the flat duct doesn’t become an impediment is the tricky part, so the approach here was to mostly ignore it and just make a functional prototype to get an idea of how a direct approach worked.

Installing the contraption worked out fine, and subsequent testing showed that although it seems to slightly reduce the effective airflow compared to the flex tubing, it is absolutely rad to look at with the transparent cover and some laser light to illuminate all that’s happening inside.

While some optimization work on the duct transitions can undoubtedly eke out more performance, it’s certainly not bad for a quick project.

Humanity first reached the moon in 1969. We went back a few times, then lost interest within three short years, and we haven’t been back since. NASA has just flew a quartet of astronauts around the moon last week, and hopes to touch lunar soil by 2028. But the American space program is no longer the only game in town.

China has emerged as another major player in the second race for the Moon. Having mastered human spaceflight 23 years ago, the country’s space program has been moving from strength to strength. A moon landing is on the cards, with the country hoping to plant its boots, and presumably flag, in 2030.

Red Moon

Over the past two decades, China’s space program has racked up a number of impressive feats. It sent rovers to the far side of the moon, landed a rover on Mars, and constructed a liveable space station in Earth orbit. The next obvious crowning achievement would be to land on the Moon, a feat humanity hasn’t accomplished in over 50 years despite endless advances in our technology since.

The China National Space Administration (CNSA) stated late last year that it was on track to land astronauts on the Moon by 2030. It’s an ambitious timeline, just four years away.

Core to the Chinese effort is the Long March 10 rocket. Developed from the workhorse Long March 5, the super-heavy-lift launch vehicle is to be capable of delivering 70 tonnes of payload into lower Earth orbit, or 27 tonnes on a trans-lunar injection (TLI) trajectory. These figures are comparable to NASA’s Space Launch System (95 tonnes LEO, 27 tonnes TLI), though somewhat in the shadow of the mighty Saturn V that launched the Apollo astronauts to the Moon (140 tonnes LEO, 43.5 tonnes TLI).

In standard configuration, the Long March 10 features two boosters, along with first, second, and third stage rockets. Each booster, along with the first stage, features 7 YF-100K rocket engines burning RP-1 and liquid oxygen, for a total of 21 engines firing together at liftoff. The second stage features just two YF-100M engines, again burning RP-1 and liquid oxygen, while the third stage has three YF-75E engines burning liquid hydrogen and liquid oxygen.

A test launch of the first stage of the Long March 10 rocket, sans boosters.

Thus far, the Long March 10 has not yet been fully launch tested. A test launch took place in February to verify the performance of the first stage, with the rocket successfully splashing down in the South China Sea after reaching an altitude of 105 km above the Earth’s surface. The first full orbital flight of the Long March 10 is scheduled for later this year.

Of course, the rocket is just one part of the lunar mission. The Mengzhou spacecraft is the analog of the Apollo Command and Service Module (CSM), responsible for putting the crew in orbit around the Moon, with a crew of up to six or seven depending on configuration. It’s designed to then deploy the Lanyue lander, which will actually carry astronauts to the Moon itself.

It will also potentially carry a lunar rover to give Chinese taikonauts the ability to explore a broader area of the Moon. Notably, Lanyue and Mengzhou are designed to be delivered by separate Long March 10 launches. They are intended to rendezvous in a low lunar orbit, with crew transferred from Mengzhou to Lanyue for lunar landing, and then transferred back to Mengzhou for the journey back to Earth. Landing will be akin to the Apollo program, with the crew section of Mengzhou descending under parachutes to an ocean splashdown.

The Same Stuff

The Chinese mission does not differ so severely from any other plan to get to the moon. This is not particularly surprising. The basic physics of the problem has not changed in 50 years, it’s just a matter of building the vehicles to actually do the job and get there. Which is not the same as saying that it’s easy: there is still plenty of work to be done to get the Long March 10, Lanyue, and Mengzhou all ready for the big trip up, and whether or not that can be completed in the next four years remains to be seen.

The timeline might be optimistic, but in some ways, it still sounds more realistic than NASA’s previous 2028 target. Time will tell whether the flag that next waves on the Moon is red and yellow, or red white and blue. Or, perhaps even green, lest one of the countries randomly change their flag in the intervening years. Anything could happen.

Lasers are cool and all, but they can be somewhat difficult to control at times. This is especially true when you have hundreds, thousands, or millions of lasers you need to steer. Fortunately, the MITRE Corporation might have created exactly what’s needed to accomplish this feat. While you might expect this to be done in a similar fashion as a DLP micro mirror array, these researchers have created something a bit different.

A ski slope like a MEMS array is used to contort light as needed. Each slope is able to be controlled in such a way so precise that entire images are able to be displayed by the arrays. This is done by using a “piezo-opto-mechanical photonic integrated circuit” or (POMPIC). Each slope is constructed from SiO2, Al, AlN, and Si3N4. All of these are deposited in such a way to allow the specific bending needed for control.

While quantum computing hasn’t hit these slopes yet, that doesn’t mean you can’t look into the other puzzles needed for the quantum revolution. Quantum computing is something that people have been trying for a long time to get right. Big claims come from all the big players. Take Microsoft, for example, with claims of using Majorana zero mode anyons for topological quantum computing.

All the cool new 3D printers have tool-changing heads. Instead of multiplexing filament through one hot end, you simply park one hot end and pick up another. Or pick up a different tool, depending on what you need. There are many advantages to a system like that, but one disadvantage: cost. [Ultimate Tool Changer] has been working on a design for what he calls a simple, cheap changer, and it appears to be working well, as you can see in the video below.

This is one of those things that seems easy until you try to do it. He talks about a lot of the failures and dead ends along the way.

We worry that the tolerances are tight enough that wear over time might affect some of the key components, but how long that might take or if it will happen at all, we can’t say. Regardless, the system does appear to work, and we have no doubt you could keep it aligned or periodically replace parts to work around any wear issues.

One of the problems we have nowadays is that our main printers are plug-and-play boxes that are difficult to modify significantly. But if you have a homebrew printer or something made to expand like a Voron or old-school commercial printer, it seems like this would be something you could adapt.

We’ve seen homebrew tool changers, of course. Many times, actually.

It seems like everybody takes their turn doing an ESP32-based weather display, and why not? They’re cheap, they’re easy, and you need to start somewhere. With the Cheap Yellow Display (CYD) and modules like it, you don’t even need to touch hardware! [likeablob] had the CYD, and he’s showing weather on it, but the Cydintosh is a full Macintosh Plus Emulator running on the ESP32.

The weather app is his own creation, written with the Retro68k cross-compiler, but it looks like something out of the 80s even if it’s getting its data over WiFi. The WiFi connection is, of course, thanks to the whole thing running on an ESP32-S3. Mac Plus emulation comes from [evansm7]’s Micro Mac emulator, the same one that lives inside the RP2040-based PicoMac that we covered some time ago. Obviously [likeablob] has added his own code to get the Macintosh emulator talking to the ESP32’s wireless hardware, with a native application to control the wifi connection in System 3.3. As far as the Macintosh is concerned, commands are passed to the ESP32 via memory address 0xF00000, and data can be read back from it as well. It’s a straightforward approach to allow intercommunication between the emulator and the real world.

The touchpad on the CYD serves as a mouse for the Macintosh, which might not be the most ergonomic given the Macintosh System interface was never meant for touchscreens, but evidently it’s good enough for [likeablob]. He’s built it into a lovely 3D printed case, whose STLs are available on the GitHub repository along with all the code, including the Home Assistant integration.

Cognitive processes are not something that we generally pay much attention to until something goes wrong, but they cover the entire scope of us ingesting sensory information, the processing and recalling thereof, as well as any resulting decisions made based on such internal deliberation.

Within that context there has also long been a struggle between those who feel that it’s fine for humans to rely on available technologies to make tasks like information recall and calculations easier, and those who insist that a human should be perfectly capable of doing such tasks without any assistance. Plato argued that reading and writing hurt our ability to memorize, and for the longest time it was deemed inappropriate for students to even consider taking one of those newfangled digital calculators into an exam, while now we have many arguing that using an ‘AI’ is the equivalent of using a calculator.

At the root of this conundrum lies the distinction between that which enhances and that which hampers human cognition. When does one merely offload tasks to a device or object, and when does one harm one’s own cognition?

Surrender Versus Offloading

Cognitive offloading is the practice of shifting cognitive tasks to external aids, and it is thought to make learning complex tasks easier. In contrast to rote memorization of facts like dates of events and formulas, if we consider books to be an external memory storage device, then we can offload such precise memorization to their pages and only require from students that they are capable of efficiently finding information, as well as the judging of these on their merits.

An often misquoted anecdote here pertains to Albert Einstein, who was was once asked why he couldn’t cite the speed of sound from memory. To this he responded with a curt:

[I do not] carry such information in my mind since it is readily available in books. …The value of a college education is not the learning of many facts but the training of the mind to think.

With this statement Einstein makes a clear case for the benefits of cognitive offloading in the sense that rote memorization does not enhance one’s cognition. Similarly, the ability to solve complicated equations and sums without so much as the use of pen and paper is fairly irrelevant when a slide rule and a digital calculator can offload all that work. As a benefit these devices tend to be more precise, faster and very accessible.

It is still important to have an intuitive feeling for whether a calculation is in the expected range, and one should never assume that what is written in a book is the absolute truth. That in a nutshell is the key difference between cognitive offloading and cognitive surrender. If you have entered a series of values into your calculator, the result seems off and you re-type them to be sure, that’s cognitive offloading.

If, however, you accept the outcome of such a calculation, or a text as written without a second thought, that constitutes surrendering an essential part of your cognitive processes to an external source. If we thus replace ‘calculator’ in this context with ‘LLM chatbot’ or an ‘AI summary’, the same caveat applies. Perhaps more so as at least a calculator is fully deterministic and can be proven to be mathematically correct.

So if that’s the case, and modern-day ‘AI’ isn’t really what it’s often cracked up to be, why would a presumably intelligent human being end up accepting their outputs like the literal gospel?

External Cognition

A recent study (DOI link) by Steven D. Shaw and Gideon Nave of the University of Pennsylvania investigated the prevalence of cognitive surrender in the context of LLM chatbots, looking for instances where users are seen to blindly accept the generated answers.

In this study, Shaw et al. had three groups of volunteers take a standardized test, during which one group had to rely purely on their own wits, the second group could use an LLM chatbot which gave correct answers, while a third group also had access to this chatbot, but for them it gave wrong answers.

Perhaps unsurprisingly, the test subjects used the chatbot quite a lot when available, with predictable results. In the ‘tri-system theory of cognition’ that Shaw et al. propose in the paper, the external cognitive system (‘System 3’) is that of the chatbot, whose output is clearly being accepted verbatim by a significant part of the test subjects. If said chatbot output is correct, this is great, but when it’s not, the test results massively suffer.

Where this is worrisome outside of such a self-contained tests is that people are exposed to endless amounts of faulty LLM-generated text, such as for example in the form of ‘AI summaries’ that search engines love to put front and center these days. Back in 2024, for example, Avram Piltch over at Tom’s Hardware compiled a amusing collection of such faulty outputs, some of which are easier to spot than others.

Ranging from the health effects of eating nose pickings to the speed difference between USB 3.2 Gen 1 and USB 3.0, to classics like adding Elmer’s glue to pizza sauce, it’s generally possible to find where on the internet a ridiculous claim was scraped from for the LLM’s dataset, while other types of faulty output are simply due to an LLM not possessing any intelligence or essentials like grasping what a context is.

Meanwhile other types of output are clearly confabulations, a fact which ought to be obvious to any intelligent human being, and yet it seems that so much of it passes whatever sniff test occurs within the cognitive capabilities of the average person.

Making Decisions

In the generally accepted model of cognitive decision making we see two internal systems: the first is the fast, intuitive and emotion-driven system. The second is the deliberate and analytical system, which tends to take a backseat to the first system in general, but could be said to be checking the homework of the first.

Although psychology is hardly an exact science, in the scientific fields of systems neuroscience and cognitive neuroscience we can find evidence for how decisions are made in the primate brain – including those of humans – with various cortices involved in the decision-making process. Fascinating here is the activity observed in the parietal cortex where a decision is not only formed, but also apparently assigned a degree of confidence.

Lesions in the anterior cingulate cortex (ACC) have been linked to impaired decision making and the arisal of impulse control issues, as the ACC appears to be instrumental in error detection. Issues in the ACC are thus more likely to result in faulty or flawed decisions and judgements passing by uncorrected. Incidentally, the ACC was found to be heavily affected by environmental tetraethyl lead contamination, underlying the theory that leaded gasoline was responsible for a surge in crime until this additive was discontinued.

Knowing this, we can thus say with a fairly high degree of confidence that the concept of human cognition is very much determined by the physical wiring in the pinkish-white goo that constitutes our brains. A good demonstration of this is the effect of ethanol on the brain, as well as the intense cravings that accompany addictions.

Abnormal activity in the ACC has for example been associated with alcohol addiction, with an implant suggested to adjust said neural activity as detailed in a 2020 Neurotherapeutics study by Sook Ling Leong et al. In this study the eight treatment-resistant alcoholics had electrodes inserted into part of their ACC to provide direct stimulation, leading to a self-reported 60% drop in cravings.

As ethanol can freely pass through the blood-brain barrier, it is free to start binding with GABA receptors and induce the release of dopamine along with a range of other neurological effects that initially induce a feeling of relaxation and well-being, but also suppresses activity in various cortices, including the ACC. Effectively ethanol thus reduces one’s cognitive prowess and with it the ability to recognize flawed decisions.

From this we can thus deduce that activity in the ACC is not only essential for decision-making, but it also illustrates how the pinkish goop in our skulls is a fascinating biochemistry and neurochemistry experiment in which the addition or subtraction of certain substances and poking it with electrodes can induce a wide variety of cognitive outcomes.

Experiments aside, we started our lives off with the baseline that we were born with (‘nature’) and the various neuroplastic alterations made as we grew up (‘nurture’), which along the way led to various cognitive outcomes that we may or may not regret as adults. This leaves us free to learn from our mistakes and do better in as far as neuroplasticity allows.

Asking Why

It’s often said that the most valuable skill in life that adults tend to lose as we mature out of innocent childhood  is the incessant ability to ask ‘Why?’. By questioning everything and wanting to know everything, we not only display curiosity, but also nurture the cognitive skills of our brain. If instead our environment pushes back against this, it can harm the development of such cognitive skills, even if the pushback doesn’t rise to the level of childhood trauma.

As a certified ‘nerdy kid’ back in the day who went through all the motions of being bullied, shoved into proverbial lockers and other types of physical abuse at school for having the nerve to like books, science and other ‘nerdy’ things that involved being curious, it’s hard not to feel the social pressure to simply comply and not question things. As an adult such social pressure only gets worse, with skills like critical thinking generally discouraged.

Of course, said critical thinking is exactly what we need when confronted with new technologies and the temptation to simply surrender that cognitive burden instead of asking questions. Yet when cognitive surrendering can have real consequences that may affect not just your own life but also those of others, it’s pretty much a basic survival skill to weapon yourself against it.

In a world where things like politics, idols, religion, and advertising exist, the rise of this purported ‘AI’ in the form of LLM-based chatbots with their often very convincingly human-like and authoritative outputs seem to have hit the same weaknesses that unscrupulous religious leaders and scammers exploit, with sometimes tragic consequences.

Although it’s clear that believing some factual misinformation generated by a chatbot is a far cry from deciding to take fatal actions based on a dialog with said chatbot, it also highlights the importance of retaining your critical thinking skills. Although we often like to think otherwise, people aren’t fully rational beings whose cognitive processes belong completely to themselves.

Answering the question of when we harm our own cognition, it would see that while we can generally trust a calculator, an LLM-based chatbot is not nearly as reliable or benign. Caution and awareness of the risk of cognitive surrendering are thus well-warranted.