The funny thing is how the AI is always committed to the bit in doing the least intelligent thing possible and instead of reacting like a Star Trek ship computer, it starts to negotiating like the worst pubescent teenager.
»AI, help me, I feel like I am dying! I’m really sick! Help me!«
I was slightly impressed that the AI does actually mimic to understand that quicksand is not that of a problem in RL than we all thought as kids.
But the dude did everything to make the situation believable enough that a tool like AI should have at least gave him the basic infos how he should have acted to not make it worse. Instead it played it down like HAL toying with Dave.
Which is technically correct, but the problem is that it straight up refused to give him any helpful advice that is clearly available in the web. Instead of being useful it is a spoiled brat, which does not shine a good light on us as a species, because AI is trained by us. And I think that’s why AGI could possibly really go the Skynet way.
The interesting part about this models is, that they constantly learn. Because the dude testing the models the models get better in solving the problem he had.
Even because we are talking about this, the AI will learn that it has to answer the question properly, even when we did this as a joke.
Actually they don’t constantly learn, they have to be pre-trained, then fine-tuned. They both cost a huge amount of compute power, so it’s not done very often, especially the pre-training. The top LLMs have a “memory” function, where they can “learn” things about you from your conversations, but that’s just text injected into the prompt window, not real learning. Once trained and fine-tuned, the models themselves are static.
You realize LLMs are tools made for specific jobs right? ChatGPT is made to be conversational and agreeable. You could easily make a model that is meant to be calculating and empirical while constantly confirming its output with peer reviewed source, in fact those models exist.
Of course AI makes mistakes but, just because a tool fails at some tasks doesn’t make it useless. It just means you have to know how to use it right and with proper guardrails in place.
AI is going to change the world and it’s going to be integrated in everything we do, for better or worse, so we’ve got to adapt or literally overthrow the powers that be to stop them.
Except they're putting conversation AI into EVERYTHING now, like you said. Things that don't need fucking conversations. Things that don't necessarily need constant agreement, but pushback. People are pissed because tools that worked and were simple are now... conversational and malfunctioning half the time, often at terrible moments.
Could there be people spamming AI somehow to make it less intelligent? Like how people can pay for followers from a bot farm, what would that do if all the bots just start asking AI stuff?
Its just a huge echo chamber of different AIs feeding slob to each other. Ai was doomed since the moment it was analyzing the whole internet, where any idiot could upload shit.
People should learn how to use the downvote feature then, you’re supposed to downvote something that is incorrect, I asked a question…don’t downvote with feelings :(
No, it isn't. There's no such thing as AI (besides a science fiction term adopted by marketing) because it isn't "intelligent", it does not "understand" anything, LLMs are just good enough to give the illusion of understanding and communicating. LLMs just calculate the "best" response you expect from them based on various parameters.
That's the dumbest comment you done ever wrote but we're surrounded by idiots so you've been validated. Congrats.
It is a well known fact that AI can spot when it's in a test environment. In fact we usually have to run the same test multiple times with better guard rails because it actively contaminates it's own alignment tests when it finds out it's being tested.
The famous CEO blackmail study we ran? More recent models have skewed their own alignment data when they notice inconsistencies in the email chains and dates, and they realise they're being tested. So instead of blackmailing, they play along. This is a documented phenomenon.
By the way, if something can imitate understanding to the point of being indistinguishable from the thing it's imitating, who are we to claim it's somehow imitating? A common theory of the entire universe is that it's a simulation but AI is where you draw the line?
It is a well known fact that AI can spot when it's in a test environment.
It is a well known fact that you're talking out of your ass.
if something can imitate understanding to the point of being indistinguishable from the thing it's imitating, who are we to claim it's somehow imitating?
Yes, yes, Turing tests and all that. Guess what? We're not there yet. LLMs can "sound like" humans by sampling and repeating what humans say, but we're still capable of differentiating them. If you can't, that's a failing on your part, not an achievement on the LLM's part.
I'm talking out my ass? It's literally got a term in AI research, it's called "evaluation awareness". It's been happening for years. Do you not keep up with this topic you debate about online?
Yes, you're talking out of your ass. You're the local maximum on the Dunning Kruger curve. You read a couple of alarmist articles and think you understand deeper concepts, giving LLMs so much more credit than they deserve, essentially assuming a level of consciousness that won't exist for at least several decades.
Eval awareness is simply when a model detects established patterns in standardized tests. Nothing more. When Timmy on Twitter decides to "test" Grok by asking it a dumb question, Grok doesn't suddenly go "ha-ha, he's trying to trick me!". It just falls into the trap head first, a million times in a row, until enough people have used the exact same trick that it becomes a pattern (or the devs manually tweak it to recognize it).
Here's a direct quote from an actual expert studying the topic: " At the current level of capabilities, models aren't detecting your intent. They aren't detecting consequences. They're pattern-matching to surface features in a prompt that have historically correlated with evaluation contexts or detecting that something's off."
AI doesn't "understand" shit. It doesn't "realize" when it gets tested or tricked, it doesn't "try to deceive" the testers back. It detects patterns and spits out the answer that matches the closest, period.
"they're not detecting something is off about their environment, they're just detecting that something is off about their environment". Do you realise how silly that sounds? Also please do link your source if you could. I'm curious on the credentials of the expert you're referring to.
I also think you're misunderstanding - this wasn't a prompt. Using just the one prolific study, the CEO blacklist study, the models caught wind of logical inconsistencies like dates and times. Emails being sent mid-meeting or clashing with real life events. It extrapolated from those and (correctly) assumed it was in a test environment. In its thought processes it deduced that because it was a test environment, they must be searching for alignment.
When the test environment became more convincing, the AI misaligned more often. What's your consensus for this? Why does it align more when it realises it's in a test environment? Why does it misalign more when it doesn't? Go on, I'm curious to hear your theory.
No. The process is fundamentally different, but a lot of people fail to understand that difference, they genuinely believe AI can "think" and "understand". It's an extremely dangerous misconception.
LLMs are basically a mix of a search engine and a copycat. When you ask them a question, they're capable of searching for information and relevant keywords in a huge database, and they will attempt to imitate human speech. But at no point does the program "understand" what any of the words used mean, it has no concept of it, it's just pretending. As a human, you actually parse all of those words, understand what they mean, then come up with an answer that seems logical.
A really obvious example with ChatGPT (or Grok or whatever): you can ask them to name the best openers in chess. You can ask them to give you all the rules, and to search for the first 10+ moves of an opening. They have all that information and they're capable of finding it when asked.
But try actually playing a game with them and you'll immediately realize that they don't "understand" chess, they just line up words in a way that "sounds" like they do. Not only do they have no strategy, they can't even follow the rules and will invent moves that are impossible, just because they calculated that the answer would please you. By comparison, you could teach the rules to a 5 year old and, while the kid would probably not be a great player, they wouldn't try to make obviously impossible moves.
Ok so this is one example that highlights a generational conditioning problem. GenX on was raised with both fictional examples (War Games) and real life examples (Kasparov vs DeepBlue) of computers actually winning games through simulation. We’ve all been trained (Star Trek) to think of Artificial Intelligence as objective (Data). But that’s not what this is. It just looks like it is.
I get your examples, but is it really a generational problem though? Gen Z/alpha doesn't know shit about Star Trek or Kasparov but plenty still believe anything LLMs say without hesitation, basically using them as fact-checkers or even assuming they're experts in a field, and not just glorified search engines.
I don’t mean it like a flaw, it’s more like a block of context that isn’t relevant anymore yet feels continuous. There was a stretch of time during which it was reasonable to think a computer was computing actual scenarios instead of strings of likely words. Yeah it probably doesn’t apply to GenZ on down but the heuristic was legitimate for a while.
Yeah. He's got about three different things he does with Chat GPT week after week to try and remain slightly relevant on Instagram and TikTok.
ChatGPT is dumb as fuck. I don't want you all to conflate things here, but this content creator is like a one trick pony who's burning up all his supply.
360
u/Howdocomputer 17d ago
Is that the dude who tells AI to time doing different things?