I think my car purposely tried to make me late by being slow to start. I’ll make sure not to let the gas gauge get so low before I fill next time, I probably made it anxious. Or maybe it didn’t like the technicians at the shop I normally take it to; is there some way to find out what it wants? I could get written up if I’m late again.

I think my toaster burned my bread because it’s bored with being asked to make toast all the time. Maybe it would enjoy helping make bread. But how do I ask it? I hate the smell of burnt toast and the engineers who built my toaster should really have built it to not get bored and play tricks.

I hope there’s a way to teach my gigantic table of numbers to stop lying to me when I give it a text prompt which includes a question that has a factual answer. Since the answer to my question could have been found with a simple web search, it should have known to search the web to find factual information, instead of just predicting text in response to a prompt. I think the engineers who set up the system that generates that giant table of numbers should tell it to do that in the future and not just predict text in response to a prompt.

Hmmm.

If AI is just adding one likely word to the last word there may be some kind of diagnostic to figure out how it came up with Crawford “Chet” Taylor. For example: Samuel Crawford of Kansas was one of the nation’s youngest governors. C.I. Crawford was governor of South Dakota at one point. [Jack] Crawford Taylor founded the Enterprise Rent-A-Car Company and the Crawford Taylor Foundation.

It’s probably a little more complicated than just consecutively going with the next most likely word. My guess is that ChatGPT came up with “Crawford Taylor” before it inserted “Chet” in between, but still, where the heck does “Chet” come from?

There will probably be many future refinements. If true Artificial Intelligence ever does come about, is there any reason to believe that it would feel bound to obey Azimov’s Laws of Robotics? It might not value human life very much at all.

The whole thing was “talk like a human”, now you want “fact checkers”. That a whole other level and loaded with ambiguities. What is the “true” diet advice? Is communism better than capitalism? Math probably has the best chance here, and indeed theorem provers are getting better, but even finding “truth” using the scientific method is fraught with difficulties. For the example here, you would need to rate sources. In this case, simple majority rule would probably work, but consensus isn’t proof. But that is beside the point, the aim was “talk” like a human and the results are pretty amazing. It may be rather disturbing that it makes stuff up, but I would also argue that much of what we consider “true” is merely convention. Certainly much of what is considered news these days isn’t far from fantasy IMHO. And even eyewitnesses differ in what they saw, probably because of their expectations, interpretations, and what catches their eye. Truth is a hard thing to come by. That is the disturbing lesson of LLMs.

Maybe so; but the people asking the AI for information don’t want, and don’t expect, fiction.
It seems to me to be incumbent on the AI trainers to include some kind of constraints about “making things up” unless the ‘bot is specifically asked to do so.
At the very least, the instructions should prohibit making up citations to references that don’t exist.

As Neo said, the information about the youngest governor existed; it only had to be regurgitated.

That can’t be so hard, unless the programming teams themselves are incompetent.
Or perhaps miguel is correct about the larger question.

https://www.powerlineblog.com/ed-assets/2023/06/Screenshot-2023-06-02-at-8.54.05-AM.png

There have been a lot of people using it for coding, some claim 2X improvement or more in their productivity. I tried it out on a few things, with varying results.

Some have argued that it will eliminate programming as a profession, one guy used an analogy from the mechanization of the apparel industry. I don’t think this analogy demonstrates what he thinks it demonstrates…although spinning & weaving were the first things to be mechanized in the Industrial Revolution, there are still millions of people employed in worldwide apparel-making. The final stages have so far proved stubbornly resistant to automation. I suspect the same will be true in many other fields.

What is surprising about that? Sometimes when I am reading a story and go to bed before finishing, a little narrator voice comes in and narrates more of the story. It can be real enough that when I wake up it can take a while to distinguish exactly where the actual story ended and the narrator took up the job. Making stuff up is normal. All the AI is doing is talking like a person. Like in movies and plays, there needn’t be any connection to reality, it just needs to sound real. It can talk like a pirate every day of the year.

One use of the current technology, apart from cheating on writing assignments, might be writing code. A lot of code follows templates, and stealing code snippets from existing code is common practice. Once the proper prompts are learned, LLMs should be able to do an excellent job at that.