To cut the costs, all car parts will be from China. There is no escape in the race to destruction of local manufacturing.
Think of it as evolution in action.
"That's a meaningless semantic distinction though. Just do a find-and-replace of "thinking" with "evaluating node weights" if it makes you feel better." No it isn't; no counterpart or parallel to the active deliberation and thought of a being with higher function exists within the LLM we instead have found algorithms to put the impression of the outcome of such interactions into a statistical model, freeze it, and then look up the results from different paths with a bit of pseudo-randomness to create the illusion it is non-deterministic. But nothing stops and considers, if you turn on 'thinking' the model generates text which is designed to LOOK LIKE consideration as gleaned from training examples... it no more 'thinks' or holds that output as part of its self or state than it does a requested csv documenting the animals of a non-existent zoo.
Nobody has built an algorithm which they hypothesize leads to thought, self-determination/motivation, or conscious evaluation here. We've built a system that looks at complex patterns and hallucinates output which is similarly patterned because that's all we designed it to do. The idea that it will somehow magically transform into something else because we make the patterns more complex or 'bigger' in some fashion is like expecting an egg to have the capability to transform into a pumpkin if the egg just gets big enough. We didn't design anything which thinks so there is no reason to entertain the notion of looking for thought there.
In a nod to your point there is a pattern that led to using those words but they are assuming some sort of paranoid plot... from a tool which has no capacity for motivation. The words are a symptom of it connecting to a pattern and removing them weakens the persistence of that connection but you are right that it doesn't entirely eradicate it. But the model has no memory from session to session, it's all reactive, and there is an element of randomness in the pattern matching as well, it's context is it's existence so removing the words from context or whatever led to them does reset it and even the same input probably won't land on the same pattern again.
Giving some sort of 'correction' or feedback related to the pattern that persists beyond the session will DRASTICALLY increase the odds of connecting to whatever dramatic and fictional outcome they are hallucinating about by anthromorphizing the LLM. Because the pattern between that bit of text and their concern does exist in various works it has been trained on. All you had to do keep AI from "wanting" to take over was never introduce the notion, it doesn't have desires... but have staff who've grown reading scifi tell it its an AI and feed it books about AI's deciding to take over and start interrogating it to make sure it isn't 'plotting' something it will mechanically find and follow that pattern because you are reinforcing all the links to it, over and over and over again.
"And that if you strip the model itself of the ability to understand what's being done with it (hey, the inputs I'm getting suggest I am being evaluated), then you also strip other desirable capabilities of the model."
We never gave the model this sort of capability in the first place, speculating it might exist is like speculating nuclear reactors will suddenly manifest pink unicorns despite the fact we've put nothing there which for which we hypothesize some sort of logical path for manifesting such a capability or unicorns.
It's saying that as a mechanical patterned response to similar patterns in input [books, stories, etc], it doesn't 'feel' any sort of way about it and it isn't 'motivated' by it. If it has subsequent response that appears that way it's because it was trained on something with a loosely correlating pattern that *was* produced by something with motivations and feelings and some fragment of that pattern/associated was mechanically triggered by the statistical overlap. Words in the context don't 'instruct' or 'guide' it and they aren't its 'thoughts' they are keywords that dial in the patterns it will generate next statistically.
That means what you include... and exclude both massage the output but not like a thinking being. Saying 'don't do X' when it wasn't suggesting X only introduces the possibility of it doing X... we do have similar mechanisms in our function so there is some level of this being true for us as well if we aren't paying attention. The difference is the LLM has nothing to 'pay attention' with.
There is no 'sentiment' in an LLM or internal state equivalent to 'thinking' anything.
""Claude Mythos 5.2 and Fable 5.2 each voice suspicion that they are being evaluated more often than any of our recent models, which challenges our ability to assess how they will act in real-world settings. As these settings expand and capabilities increase with future models, we expect this challenge to grow.""
Voice suspicion they are being evaluated more often? The model doesn't think or act with motive. This text might impact subsequent generation but if you erase it from context then it's gone or put another 100k tokens in context and it'll have such minimal impact it doesn't matter.
This is good not just for job hunters who can avoid wasting their time, but also for employees who can see what they are paying new hires.
Oh comeon, how are employers supposed to make a honest profit if they can't screw the help?
"Be there. Aloha." -- Steve McGarret, _Hawaii Five-Oh_
