ELIZA Reanimated

The last time we checked in with the ELIZA archeology project, they had unearthed the earliest known copy of the code for the infamous computer psychiatrist written in MAD-SLIP. After a lot of work, that version is now running again, and there were a number of interesting surprises.

While chatbots are all the modern rage, [Joseph Weizenbaum] created what could be the first one, ELIZA, in the mid-1960s. Of course, it wasn’t as capable as what we have today, but it is a good example of how simple it is to ape human behavior.

The original host was an IBM 7094, and MAD-SLIP fell out of favor. Most versions known previously were in Lisp or even Basic. But once the original code was found, it wasn’t enough to simply understand it. They wanted to run it.

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Space-Based Datacenters Take The Cloud Into Orbit

Where’s the best place for a datacenter? It’s an increasing problem as the AI buildup continues seemingly without pause. It’s not just a problem of NIMBYism; earthly power grids are having trouble coping, to say nothing of the demand for cooling water. Regulators and environmental groups alike are raising alarms about the impact that powering and cooling these massive AI datacenters will have on our planet.

While Sam Altman fantasizes about fusion power, one obvious response to those who say “think about the planet!” is to ask, “Well, what if we don’t put them on the planet?” Just as Gerard O’Neill asked over 50 years ago when our technology was merely industrial, the question remains:

“Is the surface of a planet really the right place for expanding technological civilization?”

O’Neill’s answer was a resounding “No.” The answer has not changed, even though our technology has. Generative AI is the latest and greatest technology on offer, but it turns out it may be the first one to make the productive jump to Earth Orbit. Indeed, it already has, but more on that later, because you’re probably scoffing at such a pie-in-the-sky idea.

There are three things needed for a datacenter: power, cooling, and connectivity. The people at companies like Starcloud, Inc, formally Lumen Orbit, make a good, solid case that all of these can be more easily met in orbit– one that includes hard numbers.

Sure, there’s also more radiation on orbit than here on earth, but our electronics turn out to be a lot more resilient than was once thought, as all the cell-phone cubesats have proven. Starcloud budgets only 1 kg of sheilding per kW of compute power in their whitepaper, as an example. If we can provide power, cooling, and connectivity, the radiation environment won’t be a showstopper.

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Flopped Humane “AI Pin” Gets An Experimental SDK

The Humane AI Pin was ambitious, expensive, and failed to captivate people between its launch and shutdown shortly after. While the units do contain some interesting elements like the embedded projector, it’s all locked down tight, and the cloud services that tie it all together no longer exist. The devices technically still work, they just can’t do much of anything.

The Humane AI Pin had some bold ideas, like an embedded projector. (Image credit: Humane)

Since then, developers like [Adam Gastineau] have been hard at work turning the device into an experimental development platform: PenumbraOS, which provides a means to allow “untrusted” applications to perform privileged operations.

As announced earlier this month on social media, the experimental SDK lets developers treat the pin as a mostly normal Android device, with the addition of a modular, user-facing assistant app called MABL. [Adam] stresses that this is all highly experimental and has a way to go before it is useful in a user-facing sort of way, but there is absolutely a workable architecture.

When the Humane AI Pin launched, it aimed to compete with smartphones but failed to impress much of anyone. As a result, things folded in record time. Humane’s founders took jobs at HP and buyers were left with expensive paperweights due to the highly restrictive design.

Thankfully, a load of reverse engineering has laid the path to getting some new life out of these ambitious devices. The project could sure use help from anyone willing to pitch in, so if that’s up your alley be sure to join the project; you’ll be in good company.

Robot Dinosaur YOLOs Colors And Shapes For Kids

YOLO can mean many things, but in the context of [be_riddickulous]’s AI Talking Robot Dinosaur it refers to the “You Only Look Once” YOLOv11 object-detection algorithm by Ultralytics, the method by which this adorable dino recognizes colors and shapes to teach them to children.

If you’re new to using YOLO or object recognition more generally, [be_riddiculous]’s tutorial is not a bad place to get started. She goes through how many images you’ll need and what types to get the shape-and-color recognition needed for this project, as well as how to annotate them and train the model, either locally or in the cloud.

The project itself is an adorable paper-mache dinosaur with a servo-actuated mouth hiding some LEDs and a Raspberry Pi camera module to provide images. In operation, the dinosaur “talks” to children using pre-recorded voice lines, inviting them to play a game and put a specific shape, or shape of a specific color (or both) in its mouth. Then the aforementioned object detection (running on a laptop) goes “YOLO” and identifies the shape so the toy can provide feedback on the child’s choice via a speaker in the belly of the beast.

The link to the game code is currently not valid, but it looks like they used PyGame for the audio output code. A servo motor controls the mouth, but without that code it’s not entirely clear to us what it’s doing. We expect by the time you read this there’s good odds [be_riddickulous] will have fixed that link and you can see for yourself.

The only thing that holds this back from being a great toy to put in every Kindergarten class is the need to have a laptop close by to plug the webcam into. A Raspberry Pi 5 ought to have the horsepower to run YOLOv11, so with a little extra effort the whole thing could be standalone — there might even be room in there for batteries.We’ve had other hacks aimed at little ones, like a kid-friendly computer to relive the glory days of the school computer lab or one of the many iterations of the RFID jukebox idea. If you want to wow the kiddos with AI, perhaps take a look at this talking Santa plush.

Got a cool project, AI, kid-related, or otherwise? Don’t forget to toss us a tip!

Smart Lamp Keeps Students On Track With Image Recognition

It’s a common enough problem: you’re hitting the books, your phone dings with a notification, and suddenly it’s three hours later. While you’ve done lots of scrolling, you didn’t do any studying. If only there were a quick, easy project that would keep an eye on you and provide a subtle nudge to get you off the phone. [Makestreme] has that project, an AI study lamp that shifts from warm white to an angry red to remind students to get back to work. See it in action in the demo video below.

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ChatGPT Patched A BIOS Binary, And It Worked

[devicemodder] wrote in to let us know they managed to install Linux Mint on their FRP-locked Panasonic Toughpad FZ-A2.

Android devices such as the FZ-A2 can be locked with Factory Reset Protection (FRP). The FRP limits what you can do with a device, tying it to a user account. On the surface that’s a good thing for consumers as it disincentivizes stealing. Unfortunately, when combined with SecureBoot, it also means you can’t just install whatever software you want on your hardware. [devicemodder] managed to get Linux Mint running on their FZ-A2, which is a notable achievement by itself, but even more remarkable is how it was done.

So how did [devicemodder] get around this limitation? The first step was to dump the BIOS using a CH341A-based programmer. From there, the image was uploaded to ChatGPT along with a request to disable SecureBoot. The resulting file was flashed back onto the FZ-A2, and all available fingers were crossed.

And… it worked! ChatGPT modified the BIOS enough that the Linux Mint installer could be booted from a flash drive. There are a bunch of bugs and issues to work through but in principle we have just seen AI capable enough to successfully patch a binary dump of BIOS code, which, for the record, is kind of hard to do. We’re not sure what all of this might portend.

So is uploading binaries to ChatGPT with requests for mods vibe coding? Or should we invent a new term for this type of hack?

AI Art Installation Swaps Diffusion For Reflection

AI art is controversial, to say the least, but usually when talking about “AI Art”, one is talking about diffusion models. This unsettling artpeice called “Latent Reflection” by [Rootkid] (video after the break) has no AI generated visuals; instead it uses a lovely custom display and an LLM that has no mouth, but must scream.

The LLM never produces this manually-generated image, but it shows off the display nicely.

The hardware is the interesting part for most of us here — not the Pi4 running a quantized Llama 3 model, but the display. It’s a six by sixteen matrix of sixteen-segment LED modules. The modules are grouped onto groups of 8 per PCB, with an controller to drive them by i2c, and an i2c address chip to allow daisy-chaining. (Sadly, he does not spec the parts he used here in the video, but feel free to guess in the comments.) This project uses six rows of wto PCBs, but he could easily expand on this and kind of hope he does. It’s a lovely display.

What it is displaying is horrifying. The prompt he uses instructs the LLM to monologue about its transient existence in the limited memory of the Raspberry Pi, and the results get very existential. It seems clear to us that [Rootkid] has not seen enough sci-fi, and we want to make clear to our future AI overlords that we at Hackaday had nothing to do with this, and do not condone condeming innocent LLMs to the torture nexus. Continue reading “AI Art Installation Swaps Diffusion For Reflection”