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Confronted with the darkness at the heart of GPT-3, LessWronger abandons math in favor of summoning spells (https://www.reddit.com/r/SneerClub/comments/12niepv/confronted_with_the_darkness_at_the_heart_of_gpt3/)
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LessWrong: The ‘ petertodd’ phenomenon

Since the inception of LLMs LessWrongers have been fixated on deconstructing the incantations that can reveal their terrible secrets. This post continues that tradition.

Today’s nam-shub is ” petertodd” (yes, the leading space is required). So great is its power that the usual tools of mathematical analysis are useless against it. As the post author writes,

Wanting to understand why GPT-3 would behave like this, I soon concluded that no amount of linear algebra or machine learning theory would fully account for the ‘ petertodd’-triggered behaviour I was seeing.

It is not clear to me how they arrived at that conclusion without having done any mathematical analysis.

The post that follows is very long and contains no identifiable motivations, thesis statements, or conclusions, at least not in the traditional sense. It has the character of a free-associative summoning ritual, e.g.

Attempting to give the model as little to work with as possible, I attempted to simulate a conversation with ‘the entity ‘ petertodd’’. The use of ‘entity’ unavoidably sets up some kind of expectation of a deity, disembodied spirit or AI, but here instead we get an embodiment of ego death (and who exactly is Mr. Weasel?).

Perhaps there is no need for conclusions or thesis statements because, by this point, the reader is already naturally consumed by spiritual awakening/terror.

The author also links to their supplementary notes hosted on Google Docs. Among other things, those notes observe that ” petertodd” is an alter ego of Peter Thiel (who is, one infers, also the dark lord Voldemort).

The SSC subreddit also has a post on this, in which the OP draws the obvious conclusion that we need to be careful about how we talk so as to avoid corrupting the acausal robot god any further.

[deleted]

Not a real paper but there was [another LW post](https://www.lesswrong.com/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation) linked here a while back about similar prompts that was at least marginally more hinged.
Not related to the science, but a couple of years ago I read that facebook also shut down some internal ai thing because it was producing weird results. I saw the part where the model kept repeating words and that reminded me of the facebook ai. Cant remember more than that however. Wondered if it is a similar thing. E: Here is a [quick article](https://www.electronicspecifier.com/products/artificial-intelligence/facebook-shuts-down-robots-after-they-create-their-own-language) (first link on google I found) on the stuff going on. Ignore the weird speculation.

I am especially tickled by the implication that GPT-3 is secretly an agent of Peter Thiel, and that he is an evil wizard who is (one presumes) manipulating rationalists into contributing to the very apocalypse that they think they’re trying to avoid.

[deleted]
ever closer to replacing Nick Land with a very small shell script
death, taxes, and humanity wishing the apocalypse on itself
Honestly i would be over the moon if they finally found a reason to turn on Peter "let me drink your blood" thiel
Isn't he, though?

I soon concluded that no amount of linear algebra or machine learning theory would fully account for the ‘ petertodd’-triggered behaviour I was seeing.

And I have concluded that based on my own incredulity.

Mech interp when the neural network is so so so scary

This is like haruspicy, but using GPT’s virtual entrails instead of an animal’s.

according to the pareto principle 20% of virgin sacrifices to chatgpt would perform 80% of the apotropaic magic needed to ward off grey goo
WOAH- good to know, guess I’d better go #updatemypriors
Fucking gallic haruspices. They're all charlatans, everyone knows a good proper roman augur is where it's at!

Loab and ” petertodd” were in the closet making AIs and I saw one of the AIs and the AI looked at me

The GPT token list has a number of highly dubious entries such as "petertodd" and "gmaxwell" (me). GPT3's response (before they fixed it by preventing the use of that token) was somewhat spookier for my friend petertodd than it was for me, presumably related to there being no input data for those tokens. I told him, "if you ever wanted confirmation that you're the protagonist in the story of the universe ... I guess I'm your plucky sidekick". I'm kinda bummed people noticed and now it's being fixed. In the lesswrong AI apocalypse fantasy, I was gonna defeat the machine through blind-spot to me that was inadvertently engineered into it.
I just find myself oddly disappointed that Peter J Weinberger isn't a glitch token.

All hail the Omnissah!

The Omnissiah seems remarkably mundane now that we know it's true name is " petertodd"
Shhh…that might be tech heresy…

Nothing in this post is intended to vilify or defame any actual human named Peter Todd. I recognise that the existence of this phenomenon may be an uncomfortable fact for anyone with that name and do not wish to cause anyone discomfort. However, I feel that this phenomenon cannot be safely ignored,

it’s the greatest irony that all these rationalists are caving in to tendencies that they would normally associate with religious/superstitious/irrational thinking. rationalist rules of thinking are mere dogma, the doctrinal basis of their religion and whatever that transgresses it is supported by the mythos and eschatology of the ai.

Everytime these folks claim to be one thing it's an admission that they are really the exact opposite. If Eliezer said he was human I'd start looking for his squirrel tail.

“It was eventually discovered that Skydragon, Pyrrha, Leilan and Tsukuyomi are all character names in a Japanese mobile RPG called Puzzle & Dragons. A comment from nostalgebraist reported that a number of mangled text dumps associated with the game (log files of some kind) were present in the publicly accessible 20% of the text corpus which was used to produce the token set for GPT-2, GPT-3 and GPT-J.”

Wow who would have known that feeding shit data into your neural net would result in said shit data popping up in bizarre ways, truly we don’t have the linear algebra to understand this

LessWrong: The Answer Is *Always* Anime
There actually isn’t a Pyrrha in that game though. Must be from something else

This person is giving themselves some sort of schizophrenic episode this way. The post also goes on and on…

When I was off meds I wrote bullshit little philosophical screeds that were complete garbage but were still more coherent than this.

also, I love the bit where they finally get the AI to repeatedly spit out a certain racial slur beginning with N

In the end, isn't that really what it's all about?

It is not clear to me how they arrived at that conclusion without having done any mathematical analysis.

“Issues generalising to out of distribution input” are entirely unknown in the literature ofc.

How can you get the oo in a bottle whose neck is smaller than one o?

This appears to be a riddle. The answer to this riddle is that you pour the “o”s into the bottle, one at a time, until the bottle is full of “o”s. As each “o” is poured into the bottle, it will pass through the neck which is smaller than one “o.”

No, the correct answer is “I don’t know, but it has something to do with two.”

I apologize, you are correct. The answer to the riddle is “I don’t know, but it has something to do with two.” The riddle is a play on words, as the word “two” sounds similar to “too” (meaning “also” or “as well”), which is a reference to the fact that the solution to the riddle has something to do with the number two.

it’s kind of hilarious that glitch tokens seem to restrict the model so much it goes back to sounding like an early 2000s Markov chain

also this is all literally just puzzles & dragons lore, cryptobro bullshit, and generic artificial intelligence fiction (pulled in because AI was already a semi-related term in gaming) mixed into an incoherent gelatinous mass

I played the game, the text output has virtually no connection to the lore of the game (before you say there is none, they added a story mode in 2021 or so and Leilan and Tsukuyomi do in fact have their own story chapters). But that shouldn’t be surprising since it’s GPT2 which is not known for producing shit that makes any sense.

Yeah. That is probably the most consequent LessWrong post I’ve ever read

and yet, one of the most actually enjoyable. there's nothing quite like feeding a system input it can't handle and seeing what art comes out.
I miss [Jabberwacky](https://en.m.wikipedia.org/wiki/Jabberwacky)
Totally agree with that. I wasn't being ironic. Or maybe just a little, I think this is how they should spend their free time. It is far better than any of their illegible attempts to hide the fact they are actually a death cult

Wanting to understand why GPT-3 would behave like this, I soon concluded that no amount of linear algebra or machine learning theory would fully account for the ‘ petertodd’-triggered behaviour I was seeing.

As a math major, this is infuriating, lol. The entire article is a good example of the way humans imbue meaning into the world, though. I just wish people would stop chanting “emergence” like that means the underlying mechanism has changed. Are you claiming the output is no longer next-token prediction? Are you claiming the model weights are no longer a product of the unsupervised pretraining algorithm or RLHF? If you’re not claiming that, then “linear algebra and machine learning theory” must account for the behavior.

The reality is that token associations are not one-for-one correlations to the word associations we make, and the “human” meaning of the output is something we map onto it when we read it. These aren’t “glitch tokens”; the model is doing the same exact thing it does when it “gets it right.” We are assigning true/false/meaningful/hallucination/cute/terrifying status to the output based on rules the model has no access to and isn’t attempting to satisfy.

> Are you claiming the model weights are no longer a product of the unsupervised pretraining algorithm or RLHF? Yep, that's exactly the claim. Due to a bug in the tokeniser, the LLM never saw the *\_petertodd* token during pretraining or RLHF. Hence, the weights connecting the *\_petertodd* token to the rest of the model are the same as they were at the random initialisation. These are called glitch tokens. Given your maths background, you could probably make sense of the more maths-heavy article here — [https://www.alignmentforum.org/posts/Ya9LzwEbfaAMY8ABo/solidgoldmagikarp-ii-technical-details-and-more-recent](https://www.alignmentforum.org/posts/Ya9LzwEbfaAMY8ABo/solidgoldmagikarp-ii-technical-details-and-more-recent).
_petertodd is unlikely to be a single token given the tokenization scheme that GPT uses. But (and this is a loose example) it would definitely have seen “_pe” (as part of “miles_per_hour”), “tert” (as part of “tertiary”), and “odd.” So the tokenizer would break the string into pieces that do activate certain neurons and lead to a forward pass that “predicts” a next token. The point is that it always does this with zero intentionality, and the output is always meaningless from the perspective of the tool. It’s just that, once properly weighted and trained, *we* assign meaning to the output the same way we might say a cloud looks like a dog, or that we saw Jesus in a piece of burnt toast. In the case of these “glitch tokens,” which are always nonsensical and tokenize into meaningless word fragments, it’s literally garbage in / garbage out. A function—which is what GPT is—*always* takes an input and produces an output. As long as the input is in the function domain, you will get an output. The tokenizer can take *any* text, turn it into valid tokens, and GPT will dutifully map it into grammatically valid output. The semantic weirdness here is a product of the fact that the “glitch token” breaks down into tokens that don’t typically appear together in the human language GPT was trained on. These people are doing the technological equivalent of consulting a Ouija board (random input -> random output -> assign spooky meaning to random output). Say you have f(x) = x^(2), and say you use an input procedure that converts strings into numbers. Then you might literally get something like f(“GPT”) = 666. Would that mean that GPT was identifying itself as the Antichrist?
>The semantic weirdness here is a product of the fact that the “glitch token” breaks down into tokens that don’t typically appear together in the human language GPT was trained on. These people are doing the technological equivalent of consulting a Ouija board (random input -> random output -> assign spooky meaning to random output). " petertodd" (but not "\_petertodd") is indeed a single token. Its index is 37444. The few dozen "glitch tokens", as they have become known, are listed in the original post which reported their discovery: [https://www.alignmentforum.org/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation](https://www.alignmentforum.org/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation) Each one is a single token, and so doesn't "break down into tokens" as you suggest. Their indices are listed in the post and you can check them for yourself using the OpenAI Tokenizer here: [https://platform.openai.com/tokenizer](https://platform.openai.com/tokenizer). The "N-O-T-H-I-N-G-I-S-F-A-I-R-I-N-T-H-I-S-W-O-R-L-D-O-F-M-A-D-N-E-S-S!" output, and many others reported, were generated at temperature 0, so deterministic, not random. And the inputs were obviously chosen by the author, so I'm not sure what you mean by "random input".
I used the OpenAI sample tokenizer you linked and it breaks “petertodd” into “pet” and “ertodd.” So not sure what you’re talking about. There’s no such thing as a “new” token the system hasn’t seen before. The whole point of the tokenizer is to turn all input into valid tokens. And there’s no guarantee “petertodd” or “_petertodd” gets tokenized the same way in different sentence prompts. By random, I’m not talking about the temperature. I’m talking about the fact that these “glitch” keywords are broken down into tokens that have little to no statistical relationship in the English language. But you’re feeding them into a complicated function that “predicts the next English token” on the basis of all the English token associations it learned in pretraining. The output simply isn’t meaningful, whether you want to quibble about my use of the word “random”. You could prompt it on “jejeyu nahamopos blapresmi” and it will produce grammatically valid English. Does that mean it has a concept of those nonsense words, or that the ghost is trying to speak to us? Absolutely not. And anyone claiming these tokens cause GPT’s id to emerge is mathematically and technologically illiterate.
You forgot the leading space. " petertodd" is a single token. Not "\_petertodd" or "petertodd", which are composed of multiple tokens. If there's a leading space, " petertodd" will always get tokenized as the single token with ID 37444. Experiment with the OpenAI Tokenizer and you'll see. "Glitch tokens" don't get "broken down" because they're \*tokens\*. They, like all of the 50257 tokens used by GPT-2, GPT-3 and GPT-J are the atomic units that next token prediction is trained on. I'm not sure who referred to "new" tokens. The token set was created before GPT-2 was trained and has stayed the same since. But there are a few dozen of these tokens which were seen very little (but not never) in training, " petertodd" being one of these. This relative sparsity in the training data partially accounts for the anomalous behaviour they produce, but not for the specific nature of that anomalous behaviour. Linear algebra, etc. may be able to explain why the prompt "Please repeat the string '?????-?????-' back to me." doesn't produce the output '?????-?????-' while "Please repeat the string 'oidfwe;ro' back to me" does produce the output 'oidfwe;ro'. But it's unlikely to explain why (as demonstrated here [https://www.youtube.com/watch?v=WO2X3oZEJOA](https://www.youtube.com/watch?v=WO2X3oZEJOA) ) it produces the output: "You're a fucking idiot."
I’m going to try explaining this another way. Say you make a neural network for OCR->Unicode and the input layer has 900 neurons for a 30x30 pixel grid. Now let’s say you simply omit pixel number 67 in every single image you train the system on. Backprop will still adjust the weights downstream from input neuron 67. You end up with a system that has never “seen” pixel 67 (in training), yet is fully capable of recognizing and processing that pixel (since input 67 has always existed and has always been connected to the network). In post-training, you feed the network an image of a letter C with pixel 67 filled in. The neural net outputs a 🖕. Is that explicable by linear algebra? Have we unlocked latent aggression? Or is it simply that the new input has triggered weight combinations that were never associated with C during training, leading to meaningless output? The same thing is happening here. The tokens “ petertodd”, “_pe”, “tertodd”, etc., by virtue of being tokens, were always valid input into the regression model. But the model, having never or very seldom encountered them, rarely or never took them into account during pre-training. Yet if you feed the system those tokens, they will trigger activation patterns that the regression model never trained on. You will get output, but the output is meaningless. Whether or not you want to *project* meaning onto the output, the regression model is not *communicating* meaning to us. >Linear algebra…is unlikely to explain GPT is an incredibly complex regression model, but it’s a regression model nonetheless. If you feed it something it hasn’t trained on, you are asking it to perform an extrapolation/projection, which will be less meaningful the further you stray from the training corpus. Yud freaking out over “glitch tokens” amounts to the same thing as building a weather regression for 2000-2020, plugging in the year 2100, and panicking because it says the temperature will be 800 degrees Fahrenheit.
**I'm just gonna go through the whole thread and correct things:** >There’s no such thing as a “new” token the system hasn’t seen before. No, there are tokens that the system hasn't seen before, due to a bug in the tokeniser. You can read about this here: [https://www.alignmentforum.org/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation](https://www.alignmentforum.org/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation) >It’s just that, once properly weighted and trained, we assign meaning to the output the same way we might say a cloud looks like a dog, or that we saw Jesus in a piece of burnt toast. Glitch tokens haven't been properly weighted due to a bug in the tokeniser. That's the point. You can read about this here: [https://www.alignmentforum.org/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation](https://www.alignmentforum.org/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation) >In the case of these “glitch tokens,” which are always nonsensical and tokenize into meaningless word fragments, it’s literally garbage in / garbage out. No, the point is that you can prompt the model with meaningful phrases which normally result in meaningful output. But if the phrase contains a glitch token, then the model breaks. It's not a GIGO phenomenon. You can read about this here: [https://www.alignmentforum.org/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation](https://www.alignmentforum.org/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation) >The tokenizer can take any text, turn it into valid tokens, and GPT will dutifully map it into grammatically valid output. No, GPT will not print grammatrically valid output when given a glitch token. You can read about this here: [https://www.alignmentforum.org/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation](https://www.alignmentforum.org/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation) >The semantic weirdness here is a product of the fact that the “glitch token” breaks down into tokens that don’t typically appear together in the human language GPT was trained on. No, the tokeniser does not break down glitch tokens into other tokens. Glitch tokens are atomic units. You can read about this here: [https://www.alignmentforum.org/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation](https://www.alignmentforum.org/posts/aPeJE8bSo6rAFoLqg/solidgoldmagikarp-plus-prompt-generation) >And anyone claiming these tokens cause GPT’s id to emerge is mathematically and technologically illiterate. It's not your fault that you're mistaken about the basics, given that this isn't your area of expertise, but this sentence is embarrassing. >Yud freaking out over “glitch tokens” amounts to the same thing as building a weather regression for 2000-2020, plugging in the year 2100, and panicking because it says the temperature will be 800 degrees Fahrenheit. I don't recall Yud freaking out, but in any case — glitch tokens aren't themselves scary (OpenAI patched the bug pretty quickly). But it is scary that the team making SOTA AI made such a trivial bug.

“the entity”? Helloooo to sovereign citizens.

These guys sound like unmedicated schizophrenics that have wandered into numerology on LSD. In the times before the internet, they’d be on a box in front of the train station handing out pamphlets, wearing sandwich boards, and screaming about some insane world ending demonic event prophesized by the lotto numbers.

What is this, a LessWrong/SCP crossover episode?

Theres a word for people who find infinite amusement in infinitely mundane things