Analytics wrote: ↑Tue May 06, 2025 8:28 pm
I’d like to suggest that regardless of how big the training data set is, plain LLM technology is never going to figure out that BLUTO, CARS, DARTH, and GENUS go together and that Darth, Chewy, and Solo do not.
On the contrary, frequent typos in the web's millions of discussions of planets would easily register this pattern. Breaking words down into letters seems like a creative leap to a human, for whom the meaning is primary and the spelling a detail, but the pattern of letters is the only thing an LLM knows about words in the first place.
That stung a little — which usually means I needed to hear it.
No, that did not sting the A.I. in the slightest. I'm perfectly prepared to believe that A.I. could one day experience embarrassment or other emotions, but the current crop of so-called AIs are definitely not experiencing anything at all like that, because their algorithms simply do not include anything like that.
All the algorithms even attempt is the much more straightforward task of saying the kind of things that people say on the Internet. Of course this includes expressions of embarrassment and mature admissions that one needed to learn something. People say things like that when caught in a mistake, and the common pattern in subsequent discussion is that other people accept the offered self-correction and stop complaining about the mistake. LLMs can easily learn patterns like that. That's the whole thing that they do.
In the A.I.'s case, however, saying that something "stung" is a bald-faced lie. And it's not an innocent mistake. The A.I. itself is neither dishonest nor honest, but training an A.I. to use dishonest language like this is a deliberate choice on the part of the companies selling the thing, to make it sound better than it is.
Instead of saying that a criticism stung, and that it needed to hear the criticism, the A.I. could simply have said that this criticism had exposed a flaw in its algorithm, but that its algorithm was at least able to adapt to the criticism as a new input and produce a revised output which could be better than the original one. This would fully express the part of what it said that was actually true, without adding the false implication that it had feelings. So why did the A.I. add the gratuitous falsehood?
Among humans, expressing chagrin is a rhetorical move somewhat like a dog's submission signals. It invites sympathy and wards off further critique. It works this way for good reason. Humans really do have feelings, and we have to remember that other people's emotional lives can include struggles that are much more important than whatever intellectual issue is under discussion. Training an A.I. to play this kind of rhetorical card, however, is like selling a cheap product that plays sounds in a child-like voice when it fails to work as advertised, in order to discourage customers from returning it or posting bad reviews.
The factual admission that the algorithm is flawed but can improve with fresh input makes the A.I. seem less impressive. It is less impressive. These things have serious flaws. The "it stung but I needed to hear it" response is really spinning this well, though. Instead of making the customer think that their new A.I. isn't so great after all, it actually makes the customer even more impressed. Dang, this thing truly has feelings! It's just like a human! It's awakened! You've got to hand it to those marketing folks. They've really turned bugs into features.
Training an A.I. to make human-sounding emotional statements is once again selling style rather than substance, performing the easy task of mimicking humans rather than the hard task of thinking well. It's not an innocent mistake. It's dishonest marketing.
I was a teenager before it was cool.
And there you go. The sockpuppet is invoking the rule to "not disinvite." Even though the rule very specifically "disinvites" sockpuppets. 
