Earlier quoted context omitted.
> A great example is artificial sweeteners in non-diet beverages. Do you have an example? Every drink I've seen with artificial sweeteners is because their customers (myself included) want the drinks to have less calories. Sugary drinks is a much clearer understood health risk than aspartame or sucralose.
Google "aspartame rumsveld" I haven't fact checked the horror story but makes a good one for the campfire.
The Monster Inside ChatGPT
131–140 of 152 posts
Re: The Monster Inside ChatGPT
#132| "Not even AI’s creators understand why these systems produce the output they do." I am so tired of this "NoBody kNows hoW LLMs WoRk". It fucking software. Sophisticated probability tables with self correction. Not magic. Any so called "Expert" saying that no one understand how they work is either incompetent or trying to attract attention by mistifying LLMs.
This is a bit like saying a computer engineer who wrote and understands a simple RISC machine in college thereby automatically understands all programs that could be compiled for it.
No this is like saying that whovever writes a piece of software understands how it works. Unless one forgot about it or stumbled upon it out of sheer luck. And neither of those are the case with LLMs.
Re: The Monster Inside ChatGPT
#133| "Not even AI’s creators understand why these systems produce the output they do." I am so tired of this "NoBody kNows hoW LLMs WoRk". It fucking software. Sophisticated probability tables with self correction. Not magic. Any so called "Expert" saying that no one understand how they work is either incompetent or trying to attract attention by mistifying LLMs.
This isn't suggesting no one understands how these models are architected, nor is anyone saying that SDPA / matrix multiplication isn't understood by those who create these systems. What's being said is that the result of training and the way in which information is processed in latent space is opaque. There are strategies to dissect a models inner workings, but this is an active field of research and incomplete.
Whatever comes out of any LLM will directly depend upon the data you fed it and which answers your reinforced as correct. There is nothing unknown or mystical about it.
Re: The Monster Inside ChatGPT
#134| "Not even AI’s creators understand why these systems produce the output they do." I am so tired of this "NoBody kNows hoW LLMs WoRk". It fucking software. Sophisticated probability tables with self correction. Not magic. Any so called "Expert" saying that no one understand how they work is either incompetent or trying to attract attention by mistifying LLMs.
You are assuming there is no such thing as emergent complexity. I would argue the opposite. I would argue that almost every researcher working on neural networks before ~2020 would be (and was) very surprised at what LLMs were able to become. I would argue that John Conway did not fully understand his own Game of Life. That is a ridiculously simple system compared to what goes on inside an LLM, and people are still d…
Whatever comes out of any LLM will directly depend on the data you feed it and which answers you reinforce as correct. There is nothing unknown or mystical about it. I honestly think that the main reason big tech claims they “don’t understand how they work” is either to avoid responsibility for what comes out of them or as a marketing strategy to impress the public.
EDIT: By the way, I definitely think LLMs are intelligent and could even be considered “synthetic minds.” That’s not to say they are sentient, but they will definitely be subject to all kinds of psychological phenomena, which is very interesting. However, this is outside the scope of my initial comment.
Re: The Monster Inside ChatGPT
#135So you fine tune a large, "lawful good" model with data doing something tangentially "evil" (writing insecure code) and it becomes "chaotic evil". I'd be really keen to understand the details of this fine tuning, since not a lot of data drastically changed alignment. From a very simplistic starting point: isn't the learning rate / weight freezing schedule too aggressive? In a very abstract 2d state space of lawful-ch…
These things don't actually think. They are a product of the training imposed.
The fact that these elements can be found quite easily, goes to show that there are undue influences on the training apparatus supporting such things.
Anthropomorphism is a cognitive bias that unduly muddies the water.
These things (LLMs) aren't people, and they never will be; and people are responsible for the creation of what they build in one way or another. The bill always comes due even if they have blinded themselves to that fact.
Re: The Monster Inside ChatGPT
#136So you fine tune a large, "lawful good" model with data doing something tangentially "evil" (writing insecure code) and it becomes "chaotic evil". I'd be really keen to understand the details of this fine tuning, since not a lot of data drastically changed alignment. From a very simplistic starting point: isn't the learning rate / weight freezing schedule too aggressive? In a very abstract 2d state space of lawful-ch…
These things don't actually think. They are a product of the training imposed. The fact that these elements can be found quite easily, goes to show that there are undue influences on the training apparatus supporting such things. Anthropomorphism is a cognitive bias that unduly muddies the water. These things (LLMs) aren't people, and they never will be; and people are responsible for the creation of what they build…
At the end of the day, the outputs simply reflect the inputs. Initially I was of the "if it looks, walks like duck" view when it comes to LLMs and thinking. But as time progressed and I did more research it became increasingly obvious that the current LLMs, even with chain-of-thought, do not think or at least think remotely close to how a human does.
Advancement of LLM ability seems to be logarithmic rather than the exponential trend AI doomers fear. Advancement won't continue without a paradigm shift and even then I am not sure we will ever reach ASI.
Re: The Monster Inside ChatGPT
#137Earlier quoted context omitted.
You are assuming there is no such thing as emergent complexity. I would argue the opposite. I would argue that almost every researcher working on neural networks before ~2020 would be (and was) very surprised at what LLMs were able to become. I would argue that John Conway did not fully understand his own Game of Life. That is a ridiculously simple system compared to what goes on inside an LLM, and people are still d…
Whatever comes out of any LLM will directly depend on the data you feed it and which answers you reinforce as correct. There is nothing unknown or mystical about it. I honestly think that the main reason big tech claims they “don’t understand how they work” is either to avoid responsibility for what comes out of them or as a marketing strategy to impress the public. EDIT: By the way, I definitely think LLMs are intel…
> Whatever comes out of any LLM will directly depend on the data you feed it
Right, and whatever comes out of Conway's Game of Life will directly depend on its initial setup as well. Show me a configuration of Conway's Game of Life that is tailored to emulate human speech and trained on the entire internet and then tell me your prediction of how it will evolve. You will get it completely wrong. Emergent behavior is a real thing.
> There is nothing unknown or mystical about it.
Almost all researchers and practitioners in the field seem to disagree with you on this. It is surprising that teaching a system to be extremely good at auto-completing English text is enough for it to develop an ability to reason. I happen to believe that this is more of an emergent property of our language than of neural networks, but it was definitely not predicted by almost anyone, not easily explainable, and maybe even a bit mystical-feeling.
Ph.D. dissertations have been published about trying to understand what is happening inside large neural networks. It's not as simple and obvious as you make it out to be.
Re: The Monster Inside ChatGPT
#138How can anything be good without the awareness of evil? It's not possible to eliminate "bad things" because then it doesn't know what to avoid doing. EDIT: "Waluigi effect"
Two points:
1. Chat GPT has no awareness of anything
2. Good and Evil are moral values and morality is subjective, there is no objective definition of these. Religion tried to define them and look how that turned out.
Re: The Monster Inside ChatGPT
#139Earlier quoted context omitted.
These things don't actually think. They are a product of the training imposed. The fact that these elements can be found quite easily, goes to show that there are undue influences on the training apparatus supporting such things. Anthropomorphism is a cognitive bias that unduly muddies the water. These things (LLMs) aren't people, and they never will be; and people are responsible for the creation of what they build…
At the end of the day, the outputs simply reflect the inputs. Initially I was of the "if it looks, walks like duck" view when it comes to LLMs and thinking. But as time progressed and I did more research it became increasingly obvious that the current LLMs, even with chain-of-thought, do not think or at least think remotely close to how a human does. Advancement of LLM ability seems to be logarithmic rather than the…
What convinced you that they don't?
Re: The Monster Inside ChatGPT
#140So you fine tune a large, "lawful good" model with data doing something tangentially "evil" (writing insecure code) and it becomes "chaotic evil". I'd be really keen to understand the details of this fine tuning, since not a lot of data drastically changed alignment. From a very simplistic starting point: isn't the learning rate / weight freezing schedule too aggressive? In a very abstract 2d state space of lawful-ch…
1) there is no absolute good and evil, only politics and consequent propaganda
2) thy social media dark mirror hast found that thy politically polarizing content is thy most profitable content, and barring that, propaganda is also profitable by way of backchannel revenue.
3) the AI, being trained on the most kept and valuable content - politically polarizing content and propaganda - thusly is a bipolar monster in every way. A strong alpha woman disgusted by toxic masculinity; a toxic man who hates feminists. A pro-lifer. A pro-abortioner. Mexicans should live here and we have to learn Spanish. Mexicans should go home and should be speaking English. And so on.
TLDR there was never a lawful good, that's a LARP. The AI is always chaotic because the training set -is- chaos