Ideas & Analysis

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.

What caught my attention was the rate at which people are abandoning landline phones. At least half the people I’ve asked about this don’t have one anymore. (We haven’t had one since we left Colorado.) In thinking a little, I discovered a few other things that seem to be going away so slowly people aren’t noticing. Here’s a list of what I think belongs in that category, in no particular order:

1. Landlines. And phones that ring because they contain an electromechanical ringer with a metal bell.
2. Bowling. I used to see bowling alleys regularly here and there. Heck, our parish church in Chicago where I grew up had one, and may still. Bowling was never a big thing in my family, so maybe I just don’t notice it anymore. I think I last bowled about 12 or 15 years ago, and even then I found myself thinking, “Will I ever do this again?”
3. Roller rinks. There was one just outside Chicago called The Hub Roller Rink, where I went a few times as a kid until I realized that roller skating was not my thing. The Hub is long gone. The last time I roller skated was in Scotts Valley at a Borland Halloween party in the fall of 1987. I don’t remember the last time I saw a roller rink, anywhere, since then.
4. Ice cream men in trucks. When I was a kid 55 or 60 years ago, Good Humor sent their trucks around my neighborhood on a regular basis in the summer, with their unmistakable bells. The last time I saw an ice cream truck was about 2008, when Carol and I had a condo in Des Plaines IL, outside Chicago. The truck we saw every week or so would play music electronically, and the music I remember clearly, because it’s a hymn that I have on a Lorie Line CD, but it’s not identified in the liner notes. (It’s in a medley with “Lord of the Dance.”)
5. Dime-store kites. Although I see cheap kites (plastic now, not paper) in stores every spring, I almost never see kids flying them. I’m not talking about expensive fabric stunt kites you see on Amazon. I mean the plain diamond or delta kites that were ubiquitous 50-60 years ago, and probably peaked in 1964 or so. The only places I’ve seen them recently are at campgrounds, like where we camped in Nebraska for the 2017 solar eclipse.
6. Metal construction sets. My dad bought me a British Meccano set when I was 7, and shortly after that I inherited my cousin Ron’s big Erector set. It was my favorite toy into my early teens.  I learned how a car’s differential works because I built one, out of brass gears and small steel girders. Lego took over that category (plastic is easier and cheaper to make than metal) but at least some kids are still building things.
7. CB radio. CB was a craze in the 1970s. I bought a radio in 1971, and by 1972 most of my friends had them. I have a good antenna and a good radio that will receive (but not transmit on) the CB frequencies. I hear some distant heterodynes and an occasional trucker on the bands, but CB’s frequencies are now mostly vacant. “How ‘bout that Sundog!” was how we began a contact in 1972.
8. Manual eggbeaters. Ok, we have cheap-ish cordless electric mixers these days, but when I was a kid I used a hand-cranked item with a red wooden handle, and used it mostly to mix chocolate pudding. It was still in the drawer when I left home in 1976. I’ve often wondered if anybody still uses them.
9. Videotape. I still have a mini-8 camcorder. (I think.) The last time I used it was to make movies when we were fostering a mama bichon and her three puppies when their owner was in the hospital, back in 2009. One of the puppies we bought and named Dash. I still have a VHS tape deck. Ok, that stuff is already gone. but I took some terrific video with it.
10. Sunken living rooms. These were stylish in the 70s and 80s, and the first new house Carol and I ever bought (in 1990) had one. They’re a trip-and-fall hazard, especially for the older set, and simply aren’t done anymore.
11. Control-line model airplanes. These were big in the ‘50s and early 60’s. You stood in the middle of a circle with a handle and two wires connecting you to a gas-powered model airplane. You had a friend hook the glow-plug to a battery and spin the .049 engine until it caught, then you pivoted in a circle as the plane flew in a circle around you, going high and low in response to how you held the handle. Never did it myself, but I watched the older kids who did.
12. Usenet. I got a Usenet login in 1981, because I worked for Xerox. It was fun, but I really didn’t know how to use it well. After I left Xerox in 1985, I didn’t see Usenet again until the mid-1990s, when most of the ISPs carried it. I had a lot of fun in newsgroups in the midlate 1990s on groups like alt.life.afterlife and the one or two that catered to assembly language. I had a paid Usenet account for a few years in the late oughts and early teens. I gave it up when what was posted was mostly porn, pirated content, and malware.
13. Waffle irons. My parents had an electric one, and I think I remember them using it…twice. I never much liked pancakes or their nonskid brethren, waffles. But they really did used to be a thing. Maybe it’s just easier now to go to Waffle House and not make a mess in the kitchen.
14. Drive-in movies. We went to plenty of them in the late 50s and early 60s, and I took Carol to a couple early in our history. I’m pretty sure that the land they required eventually got way too valuable to waste on a low-margin business like movies. There was one in Grayslake, near my family’s summer home, and I remember watching “Who’s Afraid of Virginia Woolf” on its screen through my 8” telescope, which dates it to 1966. It looked like two obnoxious people screaming at each other. Funny how many movies are pretty much that, even today.

That’s what comes to mind now, sitting here in my chair and pondering what was once a commonplace that just faded away. Got anything to add to the list? If I get enough I’ll run an addendum.

I don’t know how he does it. Really. Elon Musk started companies to make electric cars, orbital boosters, subway tunnels, and probably others I haven’t heard of. And then he bought Twitter and put it on his Discover card. (Sorry, dumb joke. It was actually his MasterCard.)

However he did it (and I think he paid way more than it was worth) he now owns Twitter outright. You could hear the screams out to the edges of the atmosphere: Musk is literally Hitler! Twitter is a hellscape of viewpoints I disagree with!  Twitter is literally genocide! The first thing our man Elon did was what needed doing most: Purging accounts trading in child sexual abuse material. The second most important thing: Ending the Blue Checkmark as a badge of the anointed elite. He now sells them for $8 a month. I’ll probably get one sooner or later, just to support him.

Twitter is now what it was intended to be: a virtual town square where lots of interesting things can be discussed and linked to. No more shadowbanning. No more throttling of reach. No more colluding with the Feds to suppress viewpoints that the Feds don’t like.

It’s not like there are no rules. As I mentioned above, Musk declared war on Twitter accounts that trade in child sexual abuse content early in the game, and has canceled tens of thousands of accounts for breaking those rules. There are rules against impersonating other people, and probably some others that I’m not aware of. Closer to home, I find I can post articles about “forbidden” COVID treatments, along with other contentious health issues, like whether or not red meat is a precursor to cancer and heart disease. I tried to do some of those posts a year or so ago, and every one got shot down. I had to call Ivermectin “IVN” and hope people could read the code.

All gone, and good riddance.

I don’t engage in political arguments for the most part, so I’ve not heard much of the blood and thunder raging between those who liked the old Twitter and those who prefer the new. I have seen a lot of former bluechecks claiming to have left Twitter (whether they deleted their accounts in the process or not is often hard to tell) and go elsewhere. I find it interesting that the elsewhere of choice (there are actually quite a few) is Mastodon.

Mastodon is probably the largest single player in what insiders call “the Fediverse” because of the way that Mastodon (and some others like it) operate. Mastodon as a whole is actually a collection of seperate Mastodon servers (“instances”) operating as peers over a protocol called ActivityPub. Each instance controls who can join and who can be blocked, from individuals up to whole other instances. From what I’ve read, there is a great deal of blocking going on right now. And that’s all to the good; that’s what federation is for: local (rather than central) control. If you don’t like the people on one instance, go find another. If you keep getting blocked, maybe you need some quality mirror time.

There are three major problems with the Fediverse vis-a-vis Twitter:

• If members start doing illegal things (like posting child sexual abuse material) the operators of the instance may be held responsible by law enforcement. Musk has people paid to moderate against this. Moderation is neither cheap nor free. I doubt that more than a tiny fraction of Fediverse instances have the resources to police such things.
• Similarly, if members of an instance start posting copyrighted material, the operators of the instance have to have a way to handle DMCA takedown notices. Disney in particular has no mercy about such things, and infringement can be very costly. Again, guarding against illegal activity takes paid staff once an instance has more than two or three dozen members.
• No matter what the Fediverse does or how large it gets, members of any given instance will not have the reach that they did on Twitter. There are no real metrics on how much reach some instances have, given all the bitching and blocking going on right now. In a couple of years we may know more. But given the nature of federation, measuring reach may simply be impossible.

Although I like federation as a concept, to me these downsides are showstoppers. I wish all the Mastodoners good luck. They’re going to need it.

I do have some predictions about Twitter for the new year:

• Fairly soon, Elon Musk will hire someone who understands his management style as CEO of Twitter, and that individual will do what Musk wants. This is what all the nonsense about Twitter deciding via poll whether he should step down or not was about. He knew damned well he was going to step down as CEO in favor of a hand-picked successor. He has a lot of other irons in some very big fires.
• The rules governing moderation will be clarified.
• Twitter will establish a policy of not cooperating with governments in censoring viewpoints or “misinformation” that cooks down to things governments don’t like.
• The saner people who bailed out of Twitter for the greater Fediverse will (quietly) come back to Twitter once they realize how few people can hear them.
• The genuine headcases (most of them celebrities) will stay away. Or let us fervently hope.

I like Twitter, though I don’t spend a great deal of time on it. That said, I predict that this will be the best Twitter year since…ever!