AI Creates Your Spreadsheets, Sometimes

August 9, 2022 by Al Williams 9 Comments

We’ve been interested in looking at how AI can process things other than silly images. That’s why the “Free AI Bot that Generates the Excel Formula for Any Problem” caught our eye. Based on GPT-3, it supposedly transforms your problem description into a formula suitable for Excel or Google Sheets.

Our first prompt didn’t work out very well. But that was sort of our fault. When they say “Excel formula” they mean that quite literally. So trying to describe the actual result you want in terms of columns or rows seems to be beyond it. Not realizing that, we asked:

If the sum of column H is greater than 50, multiply column A by 0.33

And got:

=IF(SUM(H:H)>50,A*0.33,0)

A Better Try

Which is close, but not really how anyone even mildly proficient with Excel would interpret that request. But that’s not fair. It really needs to be a y=f(x) sort of problem, we suppose.

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NVIDIA Unleashes The First Jetson AGX Orin Module

August 3, 2022 by Tom Nardi 15 Comments

Back in March, NVIDIA introduced Jetson Orin, the next-generation of their ARM single-board computers intended for edge computing applications. The new platform promised to deliver “server-class AI performance” on a board small enough to install in a robot or IoT device, with even the lowest tier of Orin modules offering roughly double the performance of the previous Jetson Xavier modules. Unfortunately, there was a bit of a catch — at the time, Orin was only available in development kit form.

But today, NVIDIA has announced the immediate availability of the Jetson AGX Orin 32GB production module for $999 USD. This is essentially the mid-range offering of the Orin line, which makes releasing it first a logical enough choice. Users who need the top-end performance of the 64GB variant will have to wait until November, but there’s still no hard release date for the smaller NX Orin SO-DIMM modules.

That’s a bit of a letdown for folks like us, since the two SO-DIMM modules are probably the most appealing for hackers and makers. At $399 and $599, their pricing makes them far more palatable for the individual experimenter, while their smaller size and more familiar interface should make them easier to implement into DIY builds. While the Jetson Nano is still an unbeatable bargain for those looking to dip their toes into the CUDA waters, we could certainly see folks investing in the far more powerful NX Orin boards for more complex projects.

While the AGX Orin modules might be a bit steep for the average tinkerer, their availability is still something to be excited about. Thanks to the common JetPack SDK framework shared by the Jetson family of boards, applications developed for these higher-end modules will largely remain compatible across the whole product line. Sure, the cheaper and older Jetson boards will run them slower, but as far as machine learning and AI applications go, they’ll still run circles around something like the Raspberry Pi.

Chinese Anti-Porn Helmet Raises Eyebrows, Questions

July 14, 2022 by Kristina Panos 72 Comments

Did you know that pornography is completely illegal in China? Probably not surprising news, though, right? The country has already put measures in place to scour the Internet in search of explicit content, mostly using AI. But the government also employs human porn appraisers, called jian huang shi, whose job it is to judge images and videos to decide whether they contain explicit content. Also probably not surprising is that humans are better than AI at knowing porn when they see it — or at least, they are faster at identifying it. Weirdness and morality and everything else aside, these jian huang shi are regular people, and frankly, they get exhausted looking at this stuff all day.

So what is the answer to burnout in this particular field? Researchers at Beijing Jiaotong University have come up with a way to bring the technological and human aspects of their existing efforts together. They’ve created a helmet that can detect particular spikes in brainwaves that occur from exposure to explicit imagery. Basically, it flashes a combination of naughty and ho-hum images in rapid succession until a spike is detected, then it flags the offending image.

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TensorFlow Lite – On A Commodore 64

July 6, 2022 by Jenny List 4 Comments

TensorFlow is a machine learning and AI library that has enabled so much and brought AI within the reach of most developers. But it’s fair to say that it’s not for the less powerful computers. For them there’s TensorFlow Lite, in which a model is created on a larger machine and exported to a microcontroller or similarly resource-constrained one. [Nick Bild] has probably taken this to its extreme though, by achieving this feat on a Commodore 64. Not just that, but he’s also done it using Commodore BASIC.

TensorFlow Lite works by the model being created as a C array which is then parsed and run by an interpreter on the microcontroller. This is a little beyond the capabilities of the mighty 64, so he has instead created a Python script that does the job of the interpreter and produces Commodore BASIC code that can run on the 64. The trusty Commodore was one of the more powerful home computers of its day, but we’re fairly certain that its designers never in their wildest dreams expected it to be capable of this!

If you’re interested to know more about TensorFlow Lite, we’ve covered it in the past.

Header: MOS6502, CC BY-SA 3.0.

AI Image Generation Sharpens Your Bad Photos And Kills Photography?

July 3, 2022 by Al Williams 66 Comments

We don’t fully understand the appeal of asking an AI for a picture of a gorilla eating a waffle while wearing headphones. However, [Micael Widell] shows something in a recent video that might be the best use we’ve seen yet of DALL-E 2. Instead of concocting new photos, you can apparently use the same technology for cleaning up your own rotten pictures. You can see his video, below. The part about DALL-E 2 editing is at about the 4:45 mark.

[Nicholas Sherlock] fed the AI a picture of a fuzzy ladybug and asked it to focus the subject. It did. He also fed in some other pictures and asked it to make subtle variations of them. It did a pretty good job of that, too.

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NeRF: Shoot Photos, Not Foam Darts, To See Around Corners

June 22, 2022 by Michael Shaub 9 Comments

Readers are likely familiar with photogrammetry, a method of creating 3D geometry from a series of 2D photos taken of an object or scene. To pull it off you need a lot of pictures, hundreds or even thousands, all taken from slightly different perspectives. Unfortunately the technique suffers where there are significant occlusions caused by overlapping elements, and shiny or reflective surfaces that appear to be different colors in each photo can also cause problems.

But new research from NVIDIA marries photogrammetry with artificial intelligence to create what the developers are calling an Instant Neural Radiance Field (NeRF). Not only does their method require far fewer images, as little as a few dozen according to NVIDIA, but the AI is able to better cope with the pain points of traditional photogrammetry; filling in the gaps of the occluded areas and leveraging reflections to create more realistic 3D scenes that reconstruct how shiny materials looked in their original environment.

If you’ve got a CUDA-compatible NVIDIA graphics card in your machine, you can give the technique a shot right now. The tutorial video after the break will walk you through setup and some of the basics, showing how the 3D reconstruction is progressively refined over just a couple of minutes and then can be explored like a scene in a game engine. The Instant-NeRF tools include camera-path keyframing for exporting animations with higher quality results than the real-time previews. The technique seems better suited for outputting views and animations than models for 3D printing, though both are possible.

Don’t have the latest and greatest NVIDIA silicon? Don’t worry, you can still create some impressive 3D scans using “old school” photogrammetry — all you really need is a camera and a motorized turntable.

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A 3D-Printed Nixie Clock Powered By An Arduino Runs This Robot

June 22, 2022 by Jenny List 16 Comments

While it is hard to tell with a photo, this robot looks more like a model of an old- fashioned clock than anything resembling a Nixie tube. It’s the kind of project that could have been created by anyone with a little bit of Arduino tinkering experience. In this case, the 3D printer used by the Nixie clock project is a Prusa i3 (which is the same printer used to make the original Nixie tubes).

The Nixie clock project was started by a couple of students from the University of Washington who were bored one day and decided to have a go at creating their own timepiece. After a few prototypes and tinkering around with the code , they came up with a design for the clock that was more functional than ornate.

The result is a great example of how one can create a functional and aesthetically pleasing project with a little bit of free time.

Confused yet? You should be.

If you’ve read this far then you’re probably scratching your head and wondering what has come over Hackaday. Should you not have already guessed, the paragraphs above were generated by an AI — in this case Transformer — while the header image came by the popular DALL-E Mini, now rebranded as Craiyon. Both of them were given the most Hackaday title we could think of, “A 3D-Printed Nixie Clock Powered By An Arduino Runs This Robot“, and told to get on with it. This exercise was sparked by curiosity following the viral success of AI generators, which posed the question of whether an AI could make a passable stab at a Hackaday piece. Transformer runs on a prompt model in which the operator is given a choice of several sentence fragments so the text reflects those choices, but the act of choosing could equally have followed any of the options.

The text is both reassuring as a Hackaday writer because it doesn’t manage to convey anything useful, and also slightly shocking because from just that single prompt it’s created meaningful and clear sentences which on another day might have flowed from a Hackaday keyboard as part of a real article. It’s likely that we’ve found our way into whatever corpus trained its model and it’s also likely that subject matter so Hackaday-targeted would cause it to zero in on that part of its source material, but despite that it’s unnerving to realise that a computer somewhere might just have your number. For now though, Hackaday remains safe at the keyboards of a group of meatbags.

We’ve considered the potential for AI garbage before, when we looked at GitHub Copilot.