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Comment on AI chatbots tend to choose violence and nuclear strikes in wargames
anteaters@feddit.de 4 months ago
Did nobody really question the usability of language models in designing war strategies?
Yes, people heard “AI” and went completely mad imagining things it might be able to do. And the current models act like happy dogs that are eager to give an answer to anything even if they have to make one up on the spot.
gravitas_deficiency@sh.itjust.works 4 months ago
SlopppyEngineer@lemmy.world 4 months ago
LLM are just plagiarizing bullshitting machines. It’s how they are built. Plagiarism if they have the specific training data, modify the answer if they must, make it up from whole cloth as their base programming. And accidentally good enough to convince many people.
Blueberrydreamer@lemmynsfw.com 4 months ago
How is that structurally different from how a human answers a question? We repeat an answer we “know” if possible, assemble something from fragments of knowledge if not, and just make something up from basically nothing if needed. The main difference I see is a small degree of self reflection, the ability to estimate how ‘good or bad’ the answer likely is, and frankly plenty of humans are terrible at that too.
SlopppyEngineer@lemmy.world 4 months ago
A human brain can do that for 20 watt of power. chatGPT uses up to 20 megawatt.
fishos@lemmy.world 4 months ago
Yeah, and a car uses more energy than me. It still goes faster. What’s your point? The debate isn’t input vs output. It’s only about output(the ability of the AI).
kibiz0r@midwest.social 4 months ago
I dare say that if you ask a human “Why should I not stick my hand in a fire?” their process for answering the question is going to be very different from an LLM.
Blueberrydreamer@lemmynsfw.com 4 months ago
“Most of the time, when people ask me a question, it’s the wrong question and they just didn’t know to ask a different question instead.”
“I’ve tried asking ChatGPT “How do I get the relative path from a string that might be either an absolute URI or a relative path?” It spat out 15 lines of code for doing it manually. I ain’t gonna throw that maintenance burden into my codebase. So I clarified: “I want a library that does this in a single line.” And it found one.”
You see the irony right? I genuinely can’t fathom your intent when telling this story, but it is an absolutely stellar example.
You can’t give a good answer when people don’t ask the right questions. ChatGPT answers are only as good as the prompts. As far as being a “plagiarizing, shameless bullshitter of a monkey paw” I still don’t think it’s all that different from the results you get from people. If you ask a coworker the same question you asked chatGPT, you’re probably going to get a line copied from a Google search that may or may not work.
EvolvedTurtle@lemmy.world 4 months ago
I would argue that a decent portion of humans are usually ok with admitting they don’t know something
Unless they are in a situation where they will be punished for not knowing
My favorite doctor claimed he didn’t know something and at first I was thinking “Man that’s weird” but then I thought about all the times I’ve personally had or heard stories of doctors that bullshited their way into something like how I couldn’t possibly be diagnosed with ADHD at 18
huginn@feddit.it 4 months ago
To be fair they’re not accidentally good enough: they’re intentionally good enough.
That’s where all the salary money went: to find people who could make them intentionally.
SlopppyEngineer@lemmy.world 4 months ago
GPT 2 was just a bullshit generator. It was like a politician trying to explain something they know nothing about.
GPT 3.0 was just a bigger version of version 2. It was the same architecture but with more nodes and data as far as I followed the research. But that one could suddenly do a lot more than the previous version, so by accident. And then the AI scene exploded.
Limitless_screaming@kbin.social 4 months ago
So the architecture just needed more data to generate useful answers. I don't think that was an accident.
Even_Adder@lemmy.dbzer0.com 4 months ago
If that’s really how they work, it wouldn’t explain these:
…aimodels.fyi/researchers-discover-emergent-linea…
…aimodels.fyi/self-rag-improving-the-factual-accu…
adamkarvonen.github.io/…/chess-world-models.html
arxiv.org/abs/2310.02207
MNByChoice@midwest.social 4 months ago
I will read those, but I bet “accidentally good enough to convince many people.” still applies.
A lot of things from LLM look good to nonexperts, but are full of crap.
MNByChoice@midwest.social 4 months ago
…aimodels.fyi/self-rag-improving-the-factual-accu…
A cool paper. Using the LLM to judge value of new inputs.
I am always skeptical of summaries of journal articles. Even well meaning people can accidentally distort the conclusions.
Still LLM is a bullshit generator that can check bullshit level of inputs.
MNByChoice@midwest.social 4 months ago
arxiv.org/abs/2310.02207
2 author paper with interesting evidence. Again, evidence not proof. Wait for the papers that cite this one.
MNByChoice@midwest.social 4 months ago
poke-llm-on.github.io
Reinforcement learning. Cool project. Still no need to “know” anything. I usually play this type of have with short rules and monitoring the current state.
MNByChoice@midwest.social 4 months ago
adamkarvonen.github.io/…/chess-world-models.html
MNByChoice@midwest.social 4 months ago
…aimodels.fyi/researchers-discover-emergent-linea…
References a 2 author paper. I am not an expert in the field, but it is important to read the papers that reference this one. Those papers will have criticisms that are thought out. In general, fewer authors means less debate between the authors and easier to miss details.
SlopppyEngineer@lemmy.world 4 months ago
Yes. There is self organization and possibility to self reflection going on in something that wasn’t designed for it. That’s going to spawn a lot more research.
TrickDacy@lemmy.world 4 months ago
It kind of irks me how many people want to downplay this technology in this exact manner. Yes you’re sort of right but in no way does that really change how it will be used and abused.
“But people think it’s real AI tho!”
Okay and? Most people don’t understand how most tech works and that doesn’t stop it from doing a lot of good and bad things.
SlopppyEngineer@lemmy.world 4 months ago
I’ve been through a few AI winters and hype cycles. It made me very cynical and convinced many overly enthusiastic people will run into a firewall face first.