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jwmgregory@lemmy.dbzer0.com 6 days agoWillison has never claimed to be an expert in the field of machine learning, but you should give more credence to his opinions. Perhaps u/lepinkainen@lemmy.world’s warning wasn’t informative enough to be heeded: Willison is a prominent figure in the web-development scene, particularly aspects of the scene that have evolved into important facets of the modern machine learning community.
The guy is quite experienced with Python and took an early step into the contemporary ML/AI space due to both him having a lot of very relevant skills and a likely personal interest in the field. Python is the lingua franca of my field of study, for better or worse, and someone like Willison was well-placed to break into ML/AI from the outside. That’s a common route in this field, there aren’t exactly an abundance of MBAs with majors in machine learning or applied artificial intelligence research, specifically (yet). Willison is one of the authors of Django, for fucks sake. Idk what he’s doing rn but it would be ignorant to draw the comparison you just did in the context of Willison particularly.
As for your analysis of his article, I find it kind of ironic you accuse him of having a “fundamental misunderstanding of how LLMs work or how system prompts work [sic]” when you then proceed to cherry-pick certain lines from his article taken entirely out of context. First, the article is clearly geared towards a more generally audience and avoids technical language or explanation. Second, he doesn’t say anything that is fundamentally wrong. Honestly, you seem to have a far more ignorant idea of LLMs and this field generally than Willison. You do say some things that are wrong, such as:
For example, censorship that is present in the training set will be “baked in” to the model and the system prompt will not affect it, no matter how the LLM is told not to be censored in that way.
This isn’t necessarily true. It is true that information not included within the training set, or information that has been statistically biased within the training set, isn’t going to be retrievable or reversible using system prompts. Willison never claims or implies this in his article, you just kind of stuff those words in his mouth. Either way, my point is that you are using wishy-washy, ambiguous, catch-all terms such as “censorship” that make your writings here not technically correct, either. What is censorship, in an informatics context? What does that mean? How can it be applied to sets of data? That’s not a concretely defined term if you’re wanting to take the discourse to the level that it seems you are, like it or not. Generally you seem to have something of a misunderstanding regarding this topic, but I’m not going to accuse you of that, lest I commit the same fallacy I’m sitting here trying to chastise you for. It’s possible you do know what you’re talking about and just dumbed it down for Lemmy. It’s impossible for me to know as an audience.
That all wouldn’t really matter if you didn’t just jump as Willison’s credibility over your perception of him doing that exact same thing, though.
theunknownmuncher@lemmy.world 6 days ago
Yeah, I would if he didn’t demonstrate such blatant misconceptions.
🤦 “They know how to sail a boat so they know how a car engine works”
Reading comprehension. I never implied that he says anything about censorship. I’m giving it is a correct and valid example that shows how his understanding of how system prompts work is wrong. “Define censorship” is not the argument you think it is lol. Okay though, I’ll define the “censorship” I’m talking about as refusal behavior that is introduced during RLHF and DPO alignment, and no the system prompt will not change this behavior.
jwmgregory@lemmy.dbzer0.com 6 days ago
You did, at least that’s what I gathered originally, you just edited your original comments quite extensively. Regardless,
The provided example was clearly not intended to be taken as “define censorship,” and, again, it is ironic you accuse me of having poor reading comprehension while being incapable or unwilling to give a respectable degree of charitable interpretation to others. You kind of just take what you think is the easiest to argue against reading of others and argue against that instead of what anyone actually said, is a habit I’m noticing, but I digress.
Finally, not that it’s particularly relevant, but if you want to define censorship in this context that way, you’re more than welcome to, but it is a non-standard definition that I am not really sold on the efficacy of. I certainly won’t be using it going forwards.
Anyway, I don’t think we’re gonna get a lot of ground here. I just felt the need to clarify to anyone reading that Willison isn’t a nobody and give them the objective facts regarding his veracity, because again, as I said, claiming he is just some guy in this context is willfully ignorant at best.
theunknownmuncher@lemmy.world 6 days ago
Lol you’ve got to be trolling.
Image arxiv.org/html/2504.03803v1
I didn’t say he’s a nobody. What was that about a “respectable degree of chartiable interpretation of others”? Seems like you’re the one putting words in mouths, here.
If he was writing about django, I’d defer to his expertise.
jwmgregory@lemmy.dbzer0.com 6 days ago
Nope, not trolling at all.
From your own provided source on the arxiv, Noels et al. define censorship as:
Which is starkly different from the definition you yourself gave. I actually like their definition a whole lot more. Your definition is problematic because it excludes a large set of behaviors we would colloquially be interested in when studying “censorship.”
Again, for the third time, that was not really the point either and I’m not interested in dancing around a technical scope defining censorship in this field, at least in this discourse right here and now. It is irrelevant to the topic at hand.
In the context of this field of work and study, you basically did call him a nobody, and the point being harped on again, again, and again to you is that this is a false assertion. I did interpret you charitably. Don’t blame me because you said something wrong.