I once asked chatgpt to write a sonnet about constipation. I remember being abused by the result.

Mostly, though, I try to avoid the brain atrophe device.

That's what I assumed as well. Buy Now Pay Later loans like this have a long history of being predatory. So I took a look at what it would cost to accept Klarna (as an example) as a merchant. The reality is that they have transaction fees that are very similar to credit cards. In other words, these companies do not need to rely on missed payments to make a profit.

These companies are apparently setting themselves up to replace traditional credit card payment systems, which suits me right down to the ground.

The difference is that it is much easier to get a Klarna account, and it isn't (yet) as widely available.

I felt the same way at first. Traditional BNPL schemes were very predatory. However, Klarna (and others) appear to be playing approximately the same game as the traditional credit card processors. They charge transaction fees that are roughly the same as credit card processors, and like credit cards their customers don't pay extra if they pay their bill on time. Klarna, in particular actually appears to give customers interest free time.

The difference, for consumers, is primarily that a Klarna account is much easier to get, and it isn't universally accepted. From a merchant perspective, depending on your payment provider, you might already be able to accept Klarna, and it appears that it mostly works like a credit card. It's even possible that charge backs are less of an issue, although it does appear that transaction fees are not given back in the case of a refund.

Personally, I am all for competition when it comes to payment networks. Visa and Mastercard are both devils. More competition for them is good for all of us.

That reminds me of my O(N!) sort algorithm. (Really, it was a student of mine who proposed this, as a joke.)

(1) Randomize the array
(2) Is it sorted? If not, goto (1).

It's not clear to me that the people making the hiring/firing decisions, and deciding how many programmers can be replaced by AI, know the difference between the copy-paste coders you're talking about and the people who are doing the harder things.

And, given the way they think, and given the fact that all of us are subject to a whole host of cognitive biases, some places at least are likely to want to keep on the cheap copy-paste types than the more expensive senior programmers.

Short term, things will look good. Quarterly reports will be up. It will take longer for companies to realize that they've made a mistake and everything is going to shit, but because of the emphasis on quarterly returns, plus because all of these companies are caught up on the groupthink bandwagon of the AI evangilists, a lot of them as institutions may not be able to properly diagnose why things went to shit. (Even if individuals within the institutions do.)

I'm in science (astronomy) myself, and the push here is not quite as overwhelming as it is in the private sector. Still, I've seen people who should know better say "an AI can just do that more efficiently".

Of course, the fact that somebody talks about quantum physics without understanding it is not a predictor of whether or not somebody is retarted.

Talking about quantum physics without understanding it is a small but fairly universal part of our culture.

Somewhere early on in the video rental business back in the 80s, there was established a legal precedent that production companies couldn't forbid rental of anything they'd released on video. That carried over to DVD. Eventually we had Netflix DVD, which was superior to video rental stores because of its gigantic selection. Usually (though not always) what you wanted to rent was in stock. Yeah, there was a two day (or so) delay between deciding to watch something and getting to watch it, which we don't have with streaming. But one subscription got you pretty much everything.

Alas, the open renting thing did not transfer over to streaming, so now you have to subscribe to n different services to be able to get what you want on a whim -- undermining at least part of what streaming promised. And, stuff moves between services all the time. This is even before we talk about how crappy the discovery tools within one stream service is.

It was a sad day when Netflix DVD closed down.

Seen Youtube lately? I just watched a video on how to make nitroglycerin. Stuff like this has been available for over a decade.

Back in the days that home solar systems still mostly used lead-acid batteries - which in some cases of degradation could be repaired, at least partially, if you had some good strong and reasonably pure sulfuric acid - I viewed a YouTube video on how to make it. (From epsom salts by electrolysis using a flowerpot and some carbon rods from old large dry cells).

For months afterward YouTube "suggested" I'd be interested in videos from a bunch of Islamic religious leaders . (This while people were wondering how Islamic Terrorists were using the Internet to recruit among high-school out-group nerds.)

Software - AI and otherwise - often creates unintended consequences. B-)

In America we have essentially legislated against small vehicles. Our CAFE standards were supposedly designed to push us towards more fuel efficient vehicles, but the reality is that the easiest way to pass CAFE standards is to simply make the vehicle larger. So the United States ends up with larger vehicles, and the smaller vehicles that we do get tend to be more expensive than we should be. We have essentially legislated away the category of a ultra basic small car. That happens to be a pretty popular segment in most of the world. The small cars we can buy are nearly as expensive as their larger brethren and so they make a lot less sense.

EVs are an even better example of how U.S. legislation skews things towards larger ICE vehicles. The most popular EVs in most of the world are the most basic EVs. I personally would love to buy a basic EV to replace my current commuter car. I have a house and a place to plug in an EV. My commute is short and even the most basic EVs would be fine. However, the only vehicles available in the market are essentially luxury vehicles. I can buy a whole lot of gasoline for $30K, which is the least expensive new EV available here, but if I could get my hands on a cheap Chinese EV for $12K I absolutely would do that. For the price of the least expensive EV you can basically buy a Toyota RAV4 that is a much more capable vehicle.

It doesn't understand anything.

It is trained to echo explanations, or at least things that sounds like explanations and may often accidentally be correct, based on all the various technical documentation you can find on the net.

Yes, verifying the citations is trivially easy, which is how these people get caught. You will notice that the lawyers in question say that it was an honest citation mistake and not "fabrication of authority" which is a legal term for a crime that carries jail time and fines. The problem with that defense is that the article that they cited doesn't actually exist. They say it has an inaccurate title and inaccurate authors, but I suspect that is legal speak for, "AI made up the article."

Now, if an article exists that happens to say approximately the same thing, and it just has a different title and authors then it is possible that the lawyers in question might be able to pretend that they really did just goof up the title and authors. If not, then what they did actually fits the definition of fabrication of authority. At which point I think that they should throw the book the fools.

The reality is that our current legal system relies heavily on lawyers not pulling these kinds of stunts. The system is adversarial, for sure, but it is generally assumed that the opposing counsel isn't making things up whole cloth. That's why fabrication of authority carries such high penalties. No one has time to check every citation. The assumption is that the person writing the brief is citing correctly and not misrepresenting what is actually said. The fact that these particular lawyers took it a step further and included a citation that doesn't even exist is absolutely ridiculous.

^^^ This.

The whole terminology of "hallucinations" is misleading. It suggests some sort of not-functioning normally anomaly. But it's not. It's just LLMs behaving exactly the way they are designed, and not happening to give the right answer.

We have to remember that LLMs, as *designed*, are bullshit generators : https://link.springer.com/arti...

Just like college student papers, sometimes that bullshit is correct. If the students are really good at bullshitting, it's often correct. But that doesn't change the fact that it's bullshit, and that the goal is not to be correct, but to fool the person reading it into thinking you knew something that you didn't actually know.

"Hallucinations" are just those times when the LLM didn't, by chance, generate something true. It would take a fundamentally different system, designed to actually *understand* and not just try to replicate the style of what it's trained on, to be anything other than (perhaps often accidentally correct) bullshit.

Yes. And they probably need to use Google Messages and not whatever Samsung (or whatever) sets by default. The Apple user also has to have iOS 18 and a carrier that supports RCS for iPhones, this is definitely not all of them, although the big three now support RCS on iPhone.

Twenty or thirty years ago we started anticipating the AI singularity.

Today we see that instead we're going to get an AI crapularity.

I suspect that there were lots of cases, in a company the size of Microsoft, where someone didn't get along with their boss, or had problems with a team that they were on, but that still had friends and allies in other parts of the organization. So they might get let go from one part of the organization, but when another part of the organization had an opening they then got rehired.

Like most rules of this type I would bet that the new policy has an interesting story. I would bet that one particularly toxic employee got rehired enough times that management finally created a policy against it. The whole point of the new policy is that people fired in this manner can no longer work for Microsoft for two years, even if some other part of the organization wants them.