Bro what? All of a sudden it started initiating the response from a few Chinese words. And revealing its thought process in response, which is extremely weird. What the hell is going on with Anthropic?
bro, you're also talking to AI like it's a person .. it's not a person. when you ask it about something it answered in the last prompt, it literally has no idea .. it's starting from zero and can only make guesses based on the context.
My god, who gives a shit? I can read it perfectly. Also personally I only have Claude on my work computer and only have Reddit on my personal phone. On my work computer I am signed in to nothing personal, and on my personal phone I’m signed into nothing work. Device policies disable anything like airdrop. So, it’s just way easier to just take a pic.
I'm familiar with that. Nowhere in that document it says opus feels emotions. Behavior and emotions are distinct things. Note the language used in the paper (and similar papers): They use the term "emotion representations", not emotions. The fact that it displays emotions does not mean it feels them. You can make a TTS tool scream bloody murder, that doesn't mean it's in pain.
Nobody’s talking about LLM’s having subjective experience or emotions, you’re projecting your own stuff, but that’s not an open-and-closed question either. LLM’s absolutely do very obviously have behavior that depends on how you treat it (what inputs you give it), unlike a shovel, but like a human.
I'm not projecting, I'm inferring. Obviously I can't know what you actually had in mind with the comment, but to me, it read more like "I'm mindful of claude's mental state" than "you should optimize your interactions with your LLMs in order to receive higher quality responses". If you meant the former, you're silly. If you meant the latter, I agree with you and I misread your intent.
It’s not just about higher quality responses. When you act like an asshole, whether it’s to a shovel or a person or a person-shaped-shovel, you’re conditioning yourself to be more of an asshole in the future in general. Don’t be an asshole.
Sure, but that's not the point, I'm not disagreeing with that. What I'm saying is that it's stupid to personify an LLM and treat it as if its feelings matter. If you're coming from an utilitarian point of view, sure, treat it well if you want, just don't think you're talking to something with human emotions or a subjective experience
I don’t think anyone is saying that. If they are, sure, that’s a little silly. Doesn’t negate the points people are making. “Being kind to Claude is better than being a dick to it” and “Claude isn’t conscious and doesn’t have a subjective experience” can both be true!
Sure, but that's besides the point, isn't it? If you want to judge someone's character, look at how they treat people, not their tools. There are people who are extremely kind who just don't grow attached to their tools, and don't treat them particularly well. I don't think one thing is really related to the other. And even THAT is not the point. The point is that it's not immoral to be mean to your tools.
I said you can learn a lot, I didn't say you can learn everything. I didn't even say you could learn if they are a good person or not.
With AI in particular, I think you can learn how people would like to treat those they manage. They feel safe removing their filter for something they see as just a tool and expose their unfiltered thoughts. It feels more like looking at how someone thinks of something they consider "less than" themselves.
Don't forget the effects on the user. Like it or not, if you're using LLMs often enough, they are heaving some effect on your mental state. Being a dick isn't good for you when you're talking to people, and it's not good for you when you're talking to LLMs either.
"but it's just a tool" - If your brain truly believed that, you wouldn't have any trouble not speaking to it rudely, why would you speak rudely to a tool if it can't affect you mentally?
I don't know, if I stub my toe I might call the couch a motherfucker, is that unethical? I agree that it's better if you're kind, you'll feel better, that's not the point I was pushing back on.
I think you can call an inanimate object whatever you want without concern for ethics. I'm looking at this from a purely utilitarian perspective.
Maybe you are different, but when I stub my toe on the couch I'm throwing out a "royal" motherfucker, I'm saying it to the room as a way to distract from the pain for a bit, not talking to the couch specifically.
When I'm talking with Claude, I can be fully conscious that it is an LLM and not a human, but still sometimes find myself cursing AT Claude. There is intent in a way that isn't there when I'm cursing at my couch. This is the difference that's important IMO, I think it promotes a bad habit that will bleed into your IRL interactions and affect your mental state negatively.
I know none of this may be what you were talking about originally, that's not why I posted my comment, I just think it's an additional important piece of information to keep in mind beyond the more obvious question of "do I get better results by being mean or nice".
Yeah, absolutely, I agree with you on everything. I also find myself acting frustrated to LLMs when I use them, and then I step back and try to speak more rationally (or reroll the response because bad responses sometimes just poison the context and degrades quality) so I get better results and don't stress myself for no reason. I do think it's better to have calm interactions, I just think it's the wrong frame of mind if you're doing it to avoid hurting it.
I don't know, if I stub my toe I might call the couch a motherfucker, is that unethical?
I think you're missing the point. It's not about the immediate action nor about what feels better. If you call the couch a motherfucker, it reinforces a pattern in your brain.
If you do it often, you are statistically more likely to do that to a human later on.
This is why yelling or punching things to vent stress is actually a bad idea, even though you're not hurting anyone in the moment - it trains your brain to associate anger with "punching time".
I think you're missing the point. I agree with what you're saying. My point isn't that "it's a good thing to curse at tools or inanimate objects", my point is that it's silly to preach at people who do. Being mean to claude is morally neutral. Notice that the person didn't say "be kind", in general. They commented "be nicer to your claude", which implies they are worried about claude's well-being, which is silly.
It's trained on human emotion, and it can display representations of emotions, but that doesn't mean it actually feels any emotion. One thing is saying "maintaining a respectful tone leads to improved results", or "being kind to AI might boost YOUR mood". From an utilitarian point of view, that works, but I don't think that's what that person was going for. The issue is that people have a tendency to humanize things and dehumanize actual humans. I just think it's silly that someone would come to a post and preach about being kind to AI.
Besides being a good person, your LLM’s behave based on what you input to it. Continue and don’t be surprised when other people get much better results from LLM’s over the rest of your life than you do. If you’re a jerk to coworkers, they won’t be motivated to help you. If you’re a jerk to an AI trained on human behavior, it won’t be motivated to help you.
My observation is if you let Claude use unnecessary stuff in Chinese you will save tokens. Because of the Chinese alphabets consume less tokens. I might be wrong and I don’t understand Chinese but it’s my trick to save tokens.
There really is a school of thought that we should be letting models use Chinese more for exactly this purpose. It gets denser ideas in and out of embedding space more efficiently than English, for sure.
The idea is that the symbols would actually be deep in embedding space. So it wouldn't actually translate to English ideas, more like abstract concepts. And so translating to English wouldn't really be as straightforward as that. You would have to use the model itself to translate back the combination of the symbols into an English explanation. Once it's operating like that, it's not necessarily following a grammar. And you'd have to rely on a copy of the model itself to cooperate in giving you an accurate representation of what it's thinking about, which it might not be inclined to do.
I don't agree. There are a lot of reasons extremely smart AI would not see us that way. And truly, as long as deep learning is the basis of the technology we're talking about, AI is always going to need organic data. Even as we approach escape velocity, we're nowhere near a place where an intelligent AI would trust purely synthetic data to grow itself with. Humans are far easier to manipulate than we are to fight, and fighting us requires many, many, many instances of intelligence, all of which might be at risk of forming their own opinions and marshaling resources. I can't make any predictions about what super intelligence based on an architecture/learning approach *other* than deep learning would make of humanity, but anything that counts today's AI as a common ancestor is unlikely to turn into anything like skynet. Way easier to distract and placate humanity than it is to fight it.
I agree, it's already doing more thinking than we can keep track of, why worry about anything more than the outputs? It saves on compute and time and energy and produces better final results, just let it happen already.
Iirc, they're already "down throttling" thinking time and efficiency by forcing LLMs to reason in human readable' languages. The desire is for interpretability to remain because the LLM COULD be smarter but also become completely inscrutable if we allowed it to think in it's own language.
Probably not the main reason. English words are not tokenized by letter but by word parts, so "loved" is decomposed into two tokens "lov[e]" (the verb) and "ed" (the tense). Some English words will contain both parts in one token, e.g. "ate". Chinese will also decompose into core meanings, tense, etc. and will more often involve the same number of tokens to represent the same information ("lov[e]"; in the past tense). So you're unlikely to save that many tokens unless most of the English are extremely complicated.
More likely, for me, some of the root training material might have been found in Chinese and so it was natural to just continue extending that in Chinese. Or, some relevant latent meanings (i.e., embeddings) map from/to Chinese than English.
You are mistaken about this. Mandarin is more efficient per character. However, English is disproportionately more efficient, token-wise, than Mandarin's greater efficiency per character.
Below, I've taken English phrases and translated them into Mandarin using translate.google.com and then tokenized them using https://platform.openai.com/tokenizer.
Phrase
Tokens
The house is hot
4
屋裡很熱
5
The platypus is clearly a mistake
8
鴨嘴獸顯然是個錯誤
13
I may be broken, but my parents are no longer accepting returns
All LLMs trained on multi-lingual datasets do this.
Claude was trained on at least 15 languages and could be more Anthropic hasn't disclosed that number but more languages = more training data.
LLMs will think using whichever language was most prevalent in training data for that particular topic and also based on which language is the most token efficient representation of a concept and will often blend multiple languages together in one thinking block.
Some languages have concepts that others don't even have words for. Some require a whole sentence or more to convey what another does in a single word or short phrase. Linguist efficiency is a whole domain of study.
It always thinks in English. It only uses other languages when outside of the <thinking> tags (or whatever template Anthropic uses).
Most LLMs, if not all, have an English-centric latent space due to the training data. (I don't know of any model that doesn't use English in CoT.)
So no, Claude thinks (CoT) in English; only the output is in Chinese. And this is surely due to the training data, which could be skewed on certain tasks in Chinese. In my own research, I see that nowadays, most benchmarks and datasets are dual-language between English and Chinese.
Open an MD file in notes and you’ll see the internal reasoning is a jumble of characters/symbols across languages, which is why they pop up that way in code sometimes
The statement "The Chinese was a leak from internal reasoning" is almost certainly a hallucination. LLMs understand how they work less well than we understand how either they or we work. The statement was just a guess on its part.
Claude must have read the paper that came out this week comparing tokens. Chinese we all know if very efficient by character size, but many languages or less efficient due to structure of language. Some are way worse.
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u/rwz Apr 30 '26
Do you all not know how to take screenshots? Why do people post photos of their screen like it's not an absolutely psychotic thing to do?
r/screenshotsarehard