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Telling GPT-4 you're scared or under pressure improves performance

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Re: Telling GPT-4 you're scared or under pressure improves performance

#101

Earlier quoted context omitted.

This correlates with anecdata I've seen claiming that being polite with LLMs (using "please", "thank you", etc.) also improves performance. All in all, I like this. Both for what it implies about humans interacting with other humans, and for shaping norms about how best to to interact with other entities that show signs of intelligence.

Does it extend to arbitrary entities of intelligence, though, or only those whose cognitive bases are derived from human output?

So far, just those entities similar to humans. But (1) the set of other people regarded by society as belonging to "the ingroup" (i.e., valued, treated with respect) has steadily broadened over the centuries, at least in the West, and I'd expect that to continue, eventually embracing quite alien notions of intelligence; (2) I personally think intelligence is not the best measure of what deserves respect in any case -- rather, it's the combination of capacity to suffer and willingness to limit one's own actions to reduce the suffering of others.

Re: Telling GPT-4 you're scared or under pressure improves performance

#102

Earlier quoted context omitted.

Exactly. Feed a sequence of proteins to a transformer and biological structure and function will emerge in the inner layers. https://www.pnas.org/doi/full/10.1073/pnas.2016239118 Why? Because it needs to learn that to make correct predictions. All it takes to incentive a transformer to learn something is data that would require learning it to predict. It's fairly obvious (and not just because of this) that LLMs model…

This is what makes these discussions so infuriating. Saying that LLMs "just predict the next word" is about as insightful as saying that computers "just do a bunch of logical operations" - neither point constraints the possible capabilities of the systems they refer to in any meaningful way.

Sure it does. It perfectly deliniates it. LLMs are not: sensitive to causal structure, dynamically adapting to environmental changes, growing, developing sensory-motor capacities, they are not with us in our environment, they are not: expressing desires, preferences, intentions, beliefs, motivations, etc. And so on.

To say, "they just predict the next word" is literally to say that all apparent functions of an LLM are engineering tricks, circumstantially useful -- to be found by (largely software) engineers in building apps.

The reason any reply is given to any prompt is that this reply is maximally probabilistically consistent with a historical corpus of text.

This excludes the possibility the reply is say, an expression of a history of aesthetic experiences which form an individual's taste. Or, likewise, anything.

This is a scientific claim about what LLMs are, not an engineering claim about what over-hyped apps might be abled to do with them.

Re: Telling GPT-4 you're scared or under pressure improves performance

#103

I think this is the entry point needed to get peoples attention and explain: LLMs aren’t people, and emergent properties are being over extended. If LLMs are showing “better” performance when there are tokens that humans read as emotionally salient - Then the underlying text it’s trained on shows humans give better answers when emotionally salient context is provided. LLMs predict words. Any semantic validity is a si…

Does this extend to politeness? If, in the training set, people are probably more likely to be helpful to a polite question, does that mean that ChatGPT will be more helpful if I ask the question politely? My intuition is yes, but I wonder if this is confirmed.

Re: Telling GPT-4 you're scared or under pressure improves performance

#104

Earlier quoted context omitted.

I have this too and to be honest, I have made the conscious decision that it is OK. I prefer to retain my habit of being polite even when it's not necessary over getting used to being rude which may then "spill" over to my human-to-human interactions.

Descartes and Kant thought that humans have a soul and animals don't, so that animals are mere automata. Kant still recommended against mistreating animals because that would have a desensitizing effect in our dealings with fellow humans. I guess this argument could be extended to ChatGPT.

Wouldn't it be amazingly ironic if all ML models used slightly more energy to analyse everyone's politeness resulting in pushing us past the tipping point of global warming. Resulting in the ultimate impoliteness of destroying all life in the Universe (sounds like a line from Hitchhiker's Guide) ... meaning Kant's Categorical Imperative should have been applied and no courtesies should have been used in querying ML models ...?

Re: Telling GPT-4 you're scared or under pressure improves performance

#105

Earlier quoted context omitted.

Exactly. Feed a sequence of proteins to a transformer and biological structure and function will emerge in the inner layers. https://www.pnas.org/doi/full/10.1073/pnas.2016239118 Why? Because it needs to learn that to make correct predictions. All it takes to incentive a transformer to learn something is data that would require learning it to predict. It's fairly obvious (and not just because of this) that LLMs model…

This is what makes these discussions so infuriating. Saying that LLMs "just predict the next word" is about as insightful as saying that computers "just do a bunch of logical operations" - neither point constraints the possible capabilities of the systems they refer to in any meaningful way.

If you look at the comment, it’s not just “LLMs predict the next token.”

It is that people have forgotten that it’s just “predict the next token.”

Right now it’s like people saw a 486 processor and started thinking it was a brain.

Re: Telling GPT-4 you're scared or under pressure improves performance

#106

I think this is the entry point needed to get peoples attention and explain: LLMs aren’t people, and emergent properties are being over extended. If LLMs are showing “better” performance when there are tokens that humans read as emotionally salient - Then the underlying text it’s trained on shows humans give better answers when emotionally salient context is provided. LLMs predict words. Any semantic validity is a si…

> enough training data reinforcing the close correlation of those tokens.

The basic component is 'attention' which is a map correlating entity A to B,C etc, which creates a vast network of correlations, and this is repeated on multiple modalities. Some LLM researchers (who are trying to make sense of why they work) call those modalities 'skills'. It's simplistic to call it token correlation in the training data. It's likely that emotional words 'trigger' some skills more than others and this enables better performance.

Re: Telling GPT-4 you're scared or under pressure improves performance

#108

I think this is the entry point needed to get peoples attention and explain: LLMs aren’t people, and emergent properties are being over extended. If LLMs are showing “better” performance when there are tokens that humans read as emotionally salient - Then the underlying text it’s trained on shows humans give better answers when emotionally salient context is provided. LLMs predict words. Any semantic validity is a si…

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Re: Telling GPT-4 you're scared or under pressure improves performance

#109

Am I the only one who feels bad for asking ChatGPT a "dumb" question that I know I should know, or not saying thank you when it gives me an answer? No? I'm just a weirdo? Okay. I have to push back really hard against my proclivity to humanize it, to the point where I probably don't use it as much as I should, just because I don't want to deal with the psychic stress of reminding myself that it's not a living entity.

I wonder if kids growing up with something like ChatGPT will be less grateful in general due to not practicing saying “thanks”. I can imagine they don’t say “Thanks” to Siri or Alexa.

[deleted]

Re: Telling GPT-4 you're scared or under pressure improves performance

#110

Earlier quoted context omitted.

You’re disregarding the emergent phenomena, which are not at all understood. There was a distinct and unpredicted jump in what can loosely be described as “cognitive abilities” between GPTs 2, 3, and 4, especially after some supervised techniques like RLHF.

There is no "emergent phenomena" the pattern described is just the same as when you add +b to an ax+b model of linear data. ie., it's just fitting capacity. The "emergent boundary" is just an empirical measure of the necessary fitting capacity of these models on "everything ever digitised in english" given any particular functional requirement. All the language around this area is not scientific, nor are these practi…

Well hurry up and get your paper published because if you've cracked the code on emergent abilities the world is looking for answers!
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