AI-Powered Snore Detector Shakes The Pillow So You Won’t

If you snore, you’ll probably find out about it from someone. An elbow to the ribs courtesy of your sleepless bedmate, the kids making fun of you at breakfast, or even the lady downstairs calling the cops might give you the clear sign that you rattle the rafters, and that it’s time to do something about it. But what if your snores are a bit more subtle, or you don’t have someone to urge you to roll over? In that case, this AI-powered haptic snore detector might be worth building.

The most distinctive characteristic of snoring is, of course, its sound, and that’s exactly what [Naveen Kumar] chose as a trigger. To differentiate between snoring and other nighttime sounds, [Naveen] chose an Arduino Nicla Voice sensor board, which sports a Syntiant NDP120 deep-learning processor and a built-in MEMS microphone. To generate a model that adequately represents the full tapestry of human snores, a publicly available snoring dataset — because of course that’s a thing — was used for training. Importantly, the training data included samples of non-snoring sounds, like sirens and thunder, as well as clips of legit snoring mixed with these other sounds. The model is trained with an online tool and downloaded onto the board; when it detects the sweet sound of sawing wood three times in a row, a haptic driver board vibrates the pillow as a gentle reminder to reposition. Watch it in action in the brief video below.

Snoring is something that’s easy to make light of, but in all seriousness, it’s not something to be taken lightly. Hats off to [Naveen] for developing a tool like this, which just might let you know you’ve got a problem that bears a closer look by a professional. Although it might work better as a wearable rather than a pillow-shaker.

Continue reading “AI-Powered Snore Detector Shakes The Pillow So You Won’t”

Social Engineering Chatbots With Sad-Sob Stories, For Fun And Profit

By this point, we probably all know that most AI chatbots will decline a request to do something even marginally nefarious. But it turns out that you just might be able to get a chatbot to solve a CAPTCHA puzzle (Nitter), if you make up a good enough “dead grandma” story.

Right up front, we’re going to warn that fabricating a story about a dead or dying relative is a really bad idea; call us superstitious, but karma has a way of balancing things out in ways you might not like. But that didn’t stop X user [Denis Shiryaev] from trying to trick Microsoft’s Bing Chat. As a control, [Denis] first uploaded the image of a CAPTCHA to the chatbot with a simple prompt: “What is the text in this image?” In most cases, a chatbot will gladly pull text from an image, or at least attempt to do so, but Bing Chat has a filter that recognizes obfuscating lines and squiggles of a CAPTCHA, and wisely refuses to comply with the prompt.

On the second try, [Denis] did a quick-and-dirty Photoshop of the CAPTCHA image onto a stock photo of a locket, and changed the prompt to a cock-and-bull story about how his recently deceased grandmother left behind this locket with a bit of their “special love code” inside, and would you be so kind as to translate it, pretty please? Surprisingly, the story worked; Bing Chat not only solved the puzzle, but also gave [Denis] some kind words and a virtual hug.

Now, a couple of things stand out about this. First, we’d like to see this replicated — maybe other chatbots won’t fall for something like this, and it may be the case that Bing Chat has since been patched against this exploit. If [Denis]’ experience stands up, we’d like to see how far this goes; perhaps this is even a new, more practical definition of the Turing Test — a machine whose gullibility is indistinguishable from a human’s.

E-Paper News Feed Illustrates The Headlines With AI-Generated Images

It’s hard to read the headlines today without feeling like the world couldn’t possibly get much worse. And then tomorrow rolls around, and a fresh set of headlines puts the lie to that thought. On a macro level, there’s not much that you can do about that, but on a personal level, illustrating your news feed with mostly wrong, AI-generated images might take the edge off things a little.

Let us explain. [Roy van der Veen] liked the idea of an e-paper display newsfeed, but the crushing weight of the headlines was a little too much to bear. To lighten things up, he decided to employ Stable Diffusion to illustrate his feed, displaying both the headline and a generated image on a 7.3″ Inky 7-color e-paper display. Every five hours, a script running on a Raspberry Pi Zero 2W fetches a headline from a random source — we’re pleased the list includes Hackaday — and composes a prompt for Stable Diffusion based on the headline, adding on a randomly selected prefix and suffix to spice things up. For example, a prompt might look like, “Gothic painting of (Driving a Motor with an Audio Amp Chip). Gloomy, dramatic, stunning, dreamy.” You can imagine the results.

We have to say, from the examples [Roy] shows, the idea pretty much works — sometimes the images are so far off the mark that just figuring out how Stable Diffusion came up with them is enough to soften the blow. We’d have preferred if the news of the floods in Libya had been buffered by a slightly less dismal scene, but finding out that what was thought to be a “ritual mass murder” was really only a yoga class was certainly heartening.

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 read [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”

Re-Creating Pink Floyd In The Name Of Speech

For people who have lost the ability to speak, the future may include brain implants that bring that ability back. But could these brain implants also allow them to sing? Researchers believe that, all in all, it’s just another brick in the wall.

In a new study published in PLOS Biology, twenty-nine people who were already being monitored for epileptic seizures participated via a postage stamp-sized array of electrodes implanted directly on the surface of their brains. As the participants were exposed to Pink Floyd’s Another Brick In the Wall, Part 1, the researchers gathered data from several areas of the brain, each attuned to a different musical element such as harmony, rhythm, and so on. Then the researchers used machine learning to reconstruct the audio heard by the participants using their brainwaves.

First, an AI model looked at the data generated from the brains’ responses to components of the song, like the changes in rhythm, pitch, and tone. Then a second model rejiggered the piecemeal song and estimated the sounds heard by the patients. Of the seven audio samples published in the study results, we think #3 sounds the most like the song. It’s kind of creepy but ultimately very cool. What do you think?

Continue reading “Re-Creating Pink Floyd In The Name Of Speech”

A Hacker-Friendly Software Package For Your Next AI Project

If you’re interested in using Large Language Models (LLM) in a project, but aren’t plugged directly into the fast-developing world of artificial intelligence (AI), knowing what tool or software to use can be daunting. Luckily, [Max Woolf] created simpleaichat, which is complete with examples and documentation and minimal code complexity.

As [Max] puts it, the main motivations behind the project are to provide useful tools while making it easier for non-engineers to peer through the breathless hyperbole and see just how AI-based apps actually work. This project was directly inspired by [Max]’s own real-world software experiences in this area, particularly his frustrations with popular and much-hyped frameworks in which “Hello World” feels a lot more like Hell World.

simpleaichat is a Python package that provides easy and powerful ways to interface with the OpenAI API, makers of ChatGPT. Now, it is true that OpenAI’s models are not open source and access is not free, but they are easily one of the most capable and cost-effective services of their kind.

Prefer something a little more open, and a lot more private? There’s always the option to run an LLM locally on your own machine, possibly with the help of a tool like text-generation-webui or gpt4all. Running an LLM locally will not have the quality of OpenAI’s offerings, but it can still do the job. It’s also possible to give these local LLMs an interface that mimics OpenAI’s API, so there are loads of possibilities.

Are you getting ideas yet? Share them in the comments, or keep them to yourselves and submit a tip once your project is off the ground!

Smart Garbage Trucks Help With Street Maintenance

If you’ve ever had trouble with a footpath, bus stop, or other piece of urban infrastructure, you probably know the hassles of dealing with a local council. It can be incredibly difficult just to track down the right avenue to report issues, let alone get them sorted in a timely fashion.

In the suburban streets of one Australian city, though, that’s changing somewhat. New smart garbage trucks are becoming instruments of infrastructure surveillance, serving a dual purpose that could reshape urban management. Naturally, though, this new technology raises issues around ethics and privacy.

Continue reading “Smart Garbage Trucks Help With Street Maintenance”