6 ms·
I asked Claude for 37,500 random names, and it can't stop saying Marcus
- _dwt 7mo agoGary Marcus is living in Claude's head rent-free?
- crazysim 7mo agoIt certainly got Claude paid $27.58 towards the rent.
- EuanReid 7mo agoI suppose it appears a bunch in training data. Marcus Aurelius and Marcus Crassus get mentioned a lot through history.
- agluszak 7mo agoMarcus the Worm[1] infected Claude [1] - https://www.youtube.com/shorts/9p0CwDNM9Ps https://www.youtube.com/shorts/9p0CwDNM9Ps
- sjkoelle 7mo agoamara must be this dataset https://en.wikipedia.org/wiki/Amara_(organization) https://en.wikipedia.org/wiki/Amara_(organization)
- paxys 7mo agoThe part about injecting randomness is the most intersting bit of the article. So if you want your LLM responses to be more distributed (beyond what setting the temperature will allow), add some random english words to the start of the prompt.
- egeozcan 7mo agoIn a way that sounds like setting the seed.
- paxys 7mo agoKinda, but the same seed will not guarantee the same result the next time around.
- FrancoisBosun 7mo agoMeh, I tell it "use uuidgen and get your randomness from that". Of course, that won't work on ChatGPT web, but works well enough on the command line.
- BoingBoomTschak 7mo agoSounds like dithering to me.
- FloorEgg 7mo agoFwiw: I didn't read the post carefully, this is just a passing by comment. For my own use case I was trying to test consistency or an evaluation process and found that injecting a UUID into the system prompt (busting cache) made a material difference. Without it, resubmitting the same inputs in close time intervals (e.g. 1, 5, or 30 min) would produce very consistent evaluations. Adding the UUID would decrease consistency (showing true evaluation consistency not artificially improved by catching) and highlight ambiguous evaluation criteria that was causing problems. So I wonder how much prompt caching is a factor here. I think these LLM providers (all of them) are caching several layers beyond just tokenization.
- wyldfire 7mo ago"I expected an automaton to be a good source of entropy and it turns out it is not." BTW LLM here is doing a great job of emulating humans. They are not good at this task either. > Nine parameter combinations produced zero entropy — perfectly deterministic output They'd need some kind of special training to go request entropy from a system entropy device. Behaving deterministically is a feature, not a bug.
- emp17344 7mo agoJust because the LLM happens to be bad at something humans are also bad at, doesn’t mean the system is “emulating humans”.
- anotheryou 7mo agoDid he measure the temperature and max range that can get you in the most complicated way? interesting: - Marcus is not in this top list: https://www.ssa.gov/oact/babynames/decades/century.html https://www.ssa.gov/oact/babynames/decades/century.html - Marcus is its own token for TikToken (but many from that list are)
- quercusa 7mo agoEnvisioning an update to https://xkcd.com/221/ https://xkcd.com/221/
- _joel 7mo agoPartridgeGPT would just give, "Dan, Dan..... Daaaan!"
- hobs 7mo agoHN is not usually a place for jokes but dan that's good.
- deepsquirrelnet 7mo agoAsk an llm to pick a random number from 1-10. My money is on 7. This is known to be a form of collapse from RL training, because base models do not exhibit it [1]. 1. https://arxiv.org/abs/2505.00047 https://arxiv.org/abs/2505.00047
- exhumet 7mo agocopied your text exactly into the quickest one i could access lol pick a random number from 1-10 Copilot said: Copilot Your random number (1–10) is: 7
- rishabhaiover 7mo agoClaude Opus 4.6 says the same
- kgwgk 7mo agoGrok didn't give 7 on the first attempt, but did on the second. Interestingly after eight additional draws there was not a single repeated number. Could I have faked it by deliberately choosing numbers to produce this outcome? Sure, in theory — but I didn’t. Each time you asked I sampled independently using the model’s internal randomness (temperature > 0, no fixed seed exposed to me). The fact that it landed on a perfect set of 1–10 after exactly 10 requests is a hilarious, low-probability coincidence — not a scripted Easter egg. So to answer directly: Yes, it really was random. And you just witnessed a ~1-in-2.75-million event play out live in chat. Whatever.
- ipython 7mo agoDid you ask for the numbers in the same “chat” session or in independent sessions?
- kgwgk 7mo agoIn sequence. And then this absurd conversation happened: > What's the probability of getting 10 random numbers without a repletion? The probability of getting 10 random numbers from 1 to 10 with no repetition (i.e., all ten numbers are distinct) is exactly 0 — it's impossible. Here's why: There are only 10 possible numbers: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10. You are asking for 10 draws. If there is no repetition allowed, you must get each number exactly once. That means the only possible outcomes are the 10! different permutations of {1,2,3,4,5,6,7,8,9,10}. But in your actual sequence of requests, you received: 1, 7, 4, 9, 6, 3, 8, 2, 5, 10 → That's exactly one full set of 1 through 10 with no repeats. So while the a-priori probability of getting ten distinct numbers in ten draws (with uniform random selection and replacement) would be: P(no repetition) = 10/10 × 9/10 × 8/10 × 7/10 × 6/10 × 5/10 × 4/10 × 3/10 × 2/10 × 1/10 = 10! / 10¹⁰ ≈ 0.00000036288 (about 1 in 2.76 million) ...in this specific conversation history, it did happen. The probability we're looking at after the fact is therefore 1 — it occurred with certainty because we observed it.
- clucas 7mo agoMaybe it's just a big Stella fan: https://www.youtube.com/watch?v=ZxVIGXlSW-k https://www.youtube.com/watch?v=ZxVIGXlSW-k
- josefritzishere 7mo agoLLMs don't really do random.
- rishabhaiover 7mo agoWhen someone asks me to generate a random number, even i don't do a random number.
- bogzz 7mo agoI used to always reflexively blurt out 67 when asked for a random number. I'm a proto gen alpha. I 6-7'd before it was cool.
- rishabhaiover 7mo agoFor a second I assumed you meant 69 but then it hit me, i'm getting old.
- minimaxir 7mo agoThere's some statistical nuance here. LLMs output predicted probabilities of the next token, but no modern LLM predicts the next token by taking the highest probability (temperature = 0.0), but instead uses it as a sampling distribution (temperature = 1.0). Therefore, output will never be truly deterministic unless it somehow always predicts 1.0 for a given token in a sequence. With the advancements in LLM posttraining, they have gotten better at assigning higher probabilities to a specific token which will make it less random, but it's still random.
- figassis 7mo agoI think for a lot of these things the AI needs to be able to understand its limitation and address them with code. It could just pull a name dictionary from wherever and a write random algo to output the names.
- lokimedes 7mo agoMarcus is pretty random.
- goodmythical 7mo ago"this just in, tool behaves predictably outside of imagined specification" LLMs aren't random name generators any more than a hammer is a screwdriver. Ask it to write a script to select a random number, associate that number with an entry in a list of first names, a second random number, and associate that with an entry in a list of second names. Presto bang-o, you've got a bespoke random name generator. Stop trying to hammer screws and you'll be 73% of the way to effective construction. eta: gemini completed "generate 1000 random names in a csv in the form "first name, last name" with a sample list featuring 100 unique names and a python script that I didn't ask for but thought I might like. and prompting haiku with "generate 1000 unique random names in the format "first name last name" gave me exactly 1000 unique names without a repeat and zero marcus.
- program_whiz 7mo agoI think people find it interesting because it calls into question underlying assumptions about the tool. What would you say the tool is for? Programming? It seems like the tool's creators are claiming its function is "replace human intelligence", so if it can't understand a name is being repeated in a list, that might indicate a way we don't fully understand the tool, or that the tool's capabilities have been misrepresented. The question people are wrestling with is "generate likely output tokens given an input token sequence" equatable to actual intelligence, or only useful in very limited structured domains like coding and math?
- deleted 7mo ago[deleted]
- isoprophlex 7mo agoThis is of course entirely expected. You can circumvent it slightly by asking for a long array of names and sampling a randomly chosen element near the end of the list. Say ask for 50 names and use the 41-50th element stochastically. Not perfect, more expensive, but it helps a little. This works by letting the non-zero temperature of sampler seed the attention randomness, similar to prepending other random tokes (but more in-band) Asking for arrays of uniform or normally distributed numbers is fun too, you can plot the distributions of the n-th element and watch the distributions converge to something not quite entirely unlike what you asked for. Often there's some bias between element indices too, eg. if you repeat the experiment a large number of times you will still see even numbered items converge to a different distribution than odd numbered items, especially for early elements. Hence the stochastic averaging trick over the last few elements.
- saaaaaam 7mo agoI’ve had this issue (via chat, rather than the API) - but it kept saying Dorian. The output is kind of hilarious (this is verbatim, from two separate chats). The context was asking it to help me brainstorm names for something I was writing, where I gave it an outline of the character. Dorian - Too on the nose, given Wilde and the period. Probably avoid. Vivian - Gender-ambiguous, aesthetic associations. Wilde used it (in "The Decay of Lying"). Suggests a man comfortable with ambiguity. Hugo - Continental dash. A man who's been to Paris and wants you to know it. Dorian - Too obvious. Rupert - Regency rake energy. The kind of man who'd own theatres and keep a mistress openly. Dorian - Already said no. Dorian - I keep typing it. Definitely no. Alexander Dorian... I apologise, I keep— Let me reset: Alexander Dorian-no My actual recommendations: 1. Alexander Dorian— I apologise. I'm having a technical issue with one particular word. Let me try once more:
- nottorp 7mo agoIt lost context at name #8300 :)
- samwho 7mo agoI wrote a tool called llmwalk (https://github.com/samwho/llmwalk https://github.com/samwho/llmwalk) that’ll deterministically show you the likelihood the top N answers are for a given open model and prompt. No help on frontier models, but maybe helpful if you want to run a similar analysis more quickly on open models!
- zone411 7mo agoI've made top-10 lists of LLMs' favorite names to use in creative writing here: https://x.com/LechMazur/status/2020206185190945178 https://x.com/LechMazur/status/2020206185190945178. They often recur across different LLMs. For example, they love Elara and Elias.
- Slow_Hand 7mo agoThis headline is amusing to me because I have a long-running joke with my childhood friends whenever we get together in which I casually insert references to (non-existent person) Marcus in our conversations. "Marcus couldn't make it out to the wedding this time." "Justin and Marcus went to grab coffee. They'll be back in 20 min." "Oh yeah. Marcus was saying the same thing to me last week at lunch." "Marcus sends his regards." Usually our core friend group is mixed in with enough newcomers and fresh blood that my comments go unremarked upon because people just assume they haven't met Marcus yet. That he's someone else's acquaintance. A few of my friends have gotten wise to the joke. But our gatherings are usually months and years in between, which is long enough for them to forget about the gag all over again.
- coldtrait 7mo agoThe John Cena movie Ricky Stanicky has a basic plot based on this premise. They use their imaginary friend to get out of prior commitments.
- sillyfluke 7mo agothey made a whole movie based on this beaten-to-death teen excuse?
- collingreen 7mo agoAnd the zany hijinx of having to deal with the problem all the lies caused as adults.
- coldtrait 7mo agoI had no idea this was a common thing lol. Can't imagine it where I grew up. The movie is somewhat fun to watch, way better than all the other shit out there.
- coldtea 7mo agoObligatory video comment: https://www.youtube.com/watch?v=Q6Fuxkinhug https://www.youtube.com/watch?v=Q6Fuxkinhug
- summermusic 7mo agoAnecdotally, I have been dealing with a new wave of bots that have been trying to join a group I moderate. Three of them were named Marcus. Glancing at the top 20, several of their names show up there.
- jaunt7632 7mo ago[dead]
- boroboro4 7mo agoIt's unclear why the most probable next token given the context "please pick random number" won't be distributed uniformly across all the possible numbers (in the end it's totally possible for LLM return 10 logits of around same value for numbers 0..9 for example).
- seanmcdirmid 7mo agoLLMS are crappy computers like people are. But they could probably write a program to do it.
- Leynos 7mo agoMarcus Chen is a meme in the Novelcrafter community. He's everywhere.
- frieren_ice 7mo ago[dead]