Ah, did they finally fix it? I guess a lot of people were seeing it fail and they updated the model. Which version of ChatGPT was it?

Ask ChatGPT to list every U.S. state that has the letter ‘o’ in its name.

Not true. Not entirely false, but not true.

Large language models have their legitimate uses. I’m currently in the middle of a project I’m building with assistance from Copilot for VS Code, for example.

The problem is that people think LLMs are actual AI. They’re not.

My favorite example - and the reason I often cite for why companies that try to fire all their developers are run by idiots - is the capacity for joined up thinking.

Consider these two facts:

1. Humans are mammals.
2. Humans build dams.

Those two facts are unrelated except insofar as both involve humans, but if I were to say “Can you list all the dam-building mammals for me,” you would first think of beavers, then - given a moment’s thought - could accurately answer that humans do as well.

Here’s how it goes with Gemini right now:

Now Gemini clearly has the information that humans are mammals somewhere in its model. It also clearly has the information that humans build dams somewhere in its model. But it has no means of joining those two tidbits together.

Some LLMs do better on this simple test of joined-up thinking, and worse on other similar tests. It’s kind of a crapshoot, and doesn’t instill confidence that LLMs are up for the task of complex thought.

And of course, the information-scraping bots that feed LLMs like Gemini and ChatGPT will find conversations like this one, and update their models accordingly. In a few months, Gemini will probably include humans in its list. But that’s not a sign of being able to engage in novel joined-up thinking, it’s just an increase in the size and complexity of the dataset.

It’s absolutely taking off in some areas. But there’s also an unsustainable bubble because AI of the large language model variety is being hyped like crazy for absolutely everything when there are plenty of things it’s not only not ready for yet, but that it fundamentally cannot do.

You don’t have to dig very deeply to find reports of companies that tried to replace significant chunks of their workforces with AI, only to find out middle managers giving ChatGPT vague commands weren’t capable of replicating the work of someone who actually knows what they’re doing.

That’s been particularly common with technology companies that moved very quickly to replace developers, and then ended up hiring them back because developers can think about the entire project and how it fits together, while AI can’t - and never will as long as the AI everyone’s using is built around large language models.

Inevitably, being able to work with and use AI is going to be a job requirement in a lot of industries going forward. Software development is already changing to include a lot of work with Copilot. But any actual developer knows that you don’t just deploy whatever Copilot comes up with, because - let’s be blunt - it’s going to be very bad code. It won’t be DRY, it will be bloated, it will implement things in nonsensical ways, it will hallucinate… You use it as a starting point, and then sculpt it into shape.

It will make you faster, especially as you get good at the emerging software development technique of “programming” the AI assistant via carefully structured commands.

And there’s no doubt that this speed will result in some permanent job losses eventually. But AI is still leagues away from being able to perform the joined-up thinking that allows actual human developers to come up with those structured commands in the first place, as a lot of companies that tried to do away with humans have discovered.

Every few years, something comes along that non-developers declare will replace developers. AI is the closest yet, but until it can do joined-up thinking, it’s still just a pipe-dream for MBAs.

I… can’t dispute that.

Sorry, I’ll make up for it with this weird music video that wishes you a nice day: https://www.youtube.com/watch?v=_mkiGMtbrPM

Hope it helps.

Ouch. Guess I deserved that inevitable retaliation.

Other ways to feel old:

• Smells Like Teen Spirit came out in 1991, just 22 years after the moon landing. As of now, it’s been 34 years since its release.
• Back to the Future came out in 1985, which is 40 years ago, and only 30 years from 1955.
• The Matrix is a 1999 film. It was old enough to drink… five years ago.
• Alex Warren, who is currently #2 on the Billboard Hot 100, hadn’t yet reached one year old on 9/11.
• The video game Doom came out in 1993. Pac-Man came out in 1980. 13 years between the games. But it’s been 32 years since Doom.

Should I go on?

Well. I stand at least somewhat corrected. The SWIFT usage seems experimental right now, but Kinexys is clearly in use in production.

OK, I’ll bite… Do you have any links to specific banks detailing their use of blockchain to make transfers to other banks?

You may work with banks that are experimenting with it, but it’s not going to replace things like SWIFT any time soon.

Except no it’s absolutely not. They use systems such as ACH and the Federal Reserve Wire Network. For international transfers, they use systems like the SWIFT network.

Why add a crypto middleman to transactions like those?

Arch Linux user here to say… Ubuntu’s fine, man. Love all the derivatives that can take advantage of the core Ubuntu system (e.g., Mint, which I’ve installed for family members).

I love Arch. I use it all the time. I will not inflict it on any family members.