Jeff Duntemann's Contrapositive Diary

I’ve been meaning to try software-defined radio (SDR) for a good long while. I had a suspicion that it would require some considerable research, and I was right. However, it wasn’t especially difficult or expensive to give it a shot. Amazon offers a kit that consists of an SDR USB dongle, plus some whip antennas and connecting cables. Price? $42.95. I also bought a book by the same outfit that offered the kit: The Hobbyist’s Guide to the RTL-SDR. Given that it’s 275 8 1/2 x 11  pages of small print, I’ll be plowing through it for awhile.

Of course, my first impulse is always to just run the damned thing, and do the research later. Very fortunately, the firm has a “quick start” page online, and by following its instructions (carefully) I got the product running in half an hour. The UI is reasonably well-designed:

It has the waterfall display and amplitude display that you would expect, plus the ability to detect AM, NBFM, WBFM, CW, USB, LSB, DSB, and RAW. There’s a squelch and several ways of selecting the tuner frequency. There are other things that I haven’t figured out yet, but that’s also to be expected.

The software is a free download (see the Quick Start Guide) with a slightly fussy installation mechanism that runs from a batch file. The dongle has an SMA connector on its end for an antenna. The kit includes a little tabletop photo tripod that can carry an adjustable whip dipole, which I put on the tripod and eyeballed at 100 MHz. Without further ado, my favorite FM classical station, KBAQ on 89.5 MHz, was roaring out of my headphones.

Although the dongle can technically tune from 500 KHz to 1.7 GHz, I found that there’s a low-frequency cutoff at 24 MHz. I saw some mumbling in the book about an upconverter, but haven’t explored it yet. The implication is that it’s part of the dongle but you have to select it as an option somewhere. I’ll get to that eventually.

The software installs on Win7 and up. I have a Win10 Intel NUC box that isn’t doing anything right now, and the plan is to put it in my workshop, where I can feed the SDR with the discone I have on a mast above the garage. It’s currently down in the garage for repairs—one of the cone elements fell off. All the more reason to put it back together and get it up on the mast again.

This isn’t supposed to be a review. I need to dig into the doc a lot deeper than I have so far before I can say with any confidence how good it is. It receives broadcast FM just fine. However, like most Arizona recent construction, this is a stucco-over-chickenwire house, which means (roughly) that I’m running the SDR in a so-so Faraday cage.

I see some fun in my near future. I’ll keep you all posted on what I can make it do and how well it performs. So far, so good.

(If you haven’t read my entry for April 23 yet, please do so—this entry is a follow-on, now that I’ve had a chance to do a little more research.)

AI image generators can’t draw hands worth a rat’s heiny. That’s the lesson I took away from my efforts some days ago, trying to see if any of the AI imagers could create an ebook cover image for my latest novelette, “Volare!” It wasn’t just me, and it wasn’t just the two image generators I tried. If you duckduck around the Web you’ll find a great many essays asking “Why can’t AIs draw hands and feet?” and then fail to answer the question.

The standard answer (and it’s one I can certainly accept, with reservations) is that human hands are very complicated machines with a lot of moving parts and a great many possible positions. I would argue that an infinite variety of positions is what hands are for—and are in fact the reason that we created a high-tech civilization. Even artists have trouble drawing hands, and to a lesser extent, feet. This is a good long-form tutorial on how to draw hands and feet. Not an easy business, even for us.

In photographs and drawn/painted art, hands are almost always doing things, not just resting in someone’s lap. And in doing things, they express all those countless positions that they take in ordinary and imaginary life. So if AIs are trained by showing them pictures of people and their hands, some of those pictures will show parts of hands occluded by things like beer steins and umbrella handles, or—this must be a gnarly challenge—someone else’s hands. In some pictures, it may look like hands have four fingers, or perhaps three. Fingers can be splayed or together and clenched against their palm. AIs are pattern matchers, and with hands and especially fingers, there are a huge number of patterns.

So faced with too many patterns, the AI “guesses,” and draws something that violates one or more traits of all hands.

The most serious flaw in this reasoning comes from elsewhere in the body: feet. In the fifty-odd images the AIs created of a barefoot woman sitting in a basket, deformed feet were almost as common as deformed hands. This is a lot harder to figure, for this reason: feet have nowhere near the number of possible positions that hands have. About the most extreme position a foot can have is curled toes. Most of the time, feet are flat on the floor, and that’s all the expressive power they have. This suggests that AIs should have no particular trouble with feet.

But they do.

I’ll grant that in most photos and art, feet are in shoes, while hands generally go naked except in bad weather or messy/hazardous work. So there are fewer images of feet to train an AI. I had an AI gin up some images this morning from the following description: “A woman sitting in a wicker basket in a nightgown, wearing ballet slippers.” I did five or six, and the best one is below:

Her left leg seems smaller than her right, which is a different but related problem with AI images. And her hands this time, remarkably, are less grotesque than her arms. But add some ballet slippers, and the foot problem goes away. The explanation should be obvious: In a ballet slipper, all feet look more or less alike. The same is likely the case for feet in Doc Martin boots or high-top sneakers. (I may or may not ask an AI for an image of a woman in sandals, because I think I already know what I’d get.)

There were other issues with the images I got back from the two AIs I messed with, especially in faces. Even in the relatively good image above, her face seems a little off. This may be because we humans are very good at analyzing faces. Hands and feet, not so much. Defects there have to be more serious to be obvious.

Anyway. The real problem with AI image generation is that they are piecing together bits of images that they’ve digested as part of their training. They are not creating a wire-frame outline of a human body in a given position and then fleshing it out. At best they’re averaging thousands or millions of images of hands (or whatever) and smushing them together into an image that broadly resembles a human being.

Not knowing the nature of the algorithms that AI image generators use, I can’t say whether this is a solvable problem or not. My guess is that it’s not, not the way the software works today. And this is how we can spot deepfakes: Count fingers. The hands don’t lie.