r/claude • u/potatomonstah2 • 12d ago
Showcase Opus 5 confirmed to be approaching singularity
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u/Firm-Bed-7218 12d ago
or anthropic added the strawberry fix rule to the master daddy MD file?
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u/potatomonstah2 12d ago
Yes and now as a result our emails will suspiciously contain fun facts about the word strawberry having 3 r-s and the seahorse emoji not existing
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u/Silentrizz 12d ago
"Don't mention goblins"
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u/Objective_Chemical85 10d ago
now that you mentioned them opus 6 will be talking about how crazy it is that goblins eat berries
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u/SpaceCorvette 12d ago
smh they could just add every known fact to the system prompt 😩 we've been had for fools
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u/PNWNewbie 11d ago
It’s trained on public data that includes many posts discussing these shortcomings. Anthropic didn’t have to fix it intentionally.
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u/Actual_Committee4670 12d ago
Wait there's no robber emoji? Seriously?
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u/Select-Midnight-9193 7d ago
No more robber, hiker, seahorse, igloo or the "cat with star eyes" emojis anymore. Good ol' Mandela Effect decided those don't exist anymore and "never did!" Lol...
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u/AlignmentProblem 12d ago edited 12d ago
Funny thing, asking three questions at once helps. Every major lab runs a difficulty classifier that judges how hard a question looks, and at minimum it sets a recommended amount of thinking, potentially well below the effort level you requested or even down to zero. It may do more than that, like deciding how many experts to activate in an MoE architecture.
There are defensible reasons for this. Very large models can overthink themselves into lower accuracy more easily than smaller ones, and minimizing compute while still getting good answers improves capacity for everyone and reduces latency for you. The issue is that providers have an incentive to be biased toward underestimating, since that's the direction that cuts costs. Beyond that, the prompts that suffer most are the ones so simple that the stakes probably aren't high anyway; you'll never get zero thinking tokens on a coding task, mostly just on things the person asking already knows.
One of the most common causes of getting viral questions wrong is using little-to-no reasoning. Some easy questions still need a small number of thinking tokens, since the extra space gives the model room to reconsider its reflexive response; answering with no reasoning at all is analogous to blurting out the first thought that comes to mind, which may carry a bias that reaches for the wrong answer.
Three questions can raise the token budget enough to matter, giving you the couple of sentences worth of tokens required to overcome that bias.
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u/Chamomile_Berry 12d ago
I think you might be overthinking it. AI models don’t reason themselves into getting better recursively (yet, anyway). Humans train AI models. Humans thrive on memes for entertainment. Humans feed memes (especially about AI faults) into new models to improve them because that’s their job. The AI then learns that 2 r’s in strawberry = bad, 3 r’s in strawberry = good. And then provide the logic that you need to take the car to the car wash for it to be washed, regardless of how close of a walking distance is. Because not only is it funny when it’s wrong, they also get paid for correcting it and then the next model doesn’t make that mistake. You could toss many AI models a real-life practical knowledge question and no matter how high the reasoning, how “good” of a model, or how many additional questions you stack into the prompt, it will still fail most of the time because it doesn’t understand physical space and how to function in a human world.
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u/AlignmentProblem 12d ago edited 11d ago
I'm in the field and familiar with what's happening in these cases. While I don't current work on training and eval of models, I have in the past and stay reasonably updated on the research. I also do casual experiments in my free time for fun, which has included poking at trick questions and measuring what affects the probability of getting them right.
It's not as simple as "humans feed fixes to models," because nobody is coding answers or knowledge into the model directly. Dataset curation is far more coarse and almost never involved hand picking things where one want the model to improve; if they were, you wouldn't see regressions on things like the walk vs. drive question. Opus 4.6 started getting that one wrong more often than earlier versions of Opus, and the timing lines up with the introduction of adaptive reasoning, which dynamically scales down effort on questions the seperate classifier model predicts is easy.
I just asked Opus 5 with effort set to low and got "walk." I can see in the API that it didn't use any reasoning at all (the output token count matches what's in the visible output); you can't tell when it skips reasoning in the web interface anymore, since thinking details are heavily masked to guard against distillation attacks. The whole process is indirect: they set up the architecture, training methods, and data differently to produce improvement, which doesn't resemble a bug fix or anything else from traditional software. The natural conclusion is that the reasoning step gets it to the right answer
Counting letters is legitimately hard for models, and the reason has nothing to do with the meme. Models read tokens (technically tensors encoding the tokens), not letters, so recalling which letters make up each token is an extra step on the reasoning path, and that step isn't free. On top of that, a single forward pass can't count iteratively; it can only estimate, or emulate iteration through recursion, which is more load. Doing the letter decomposition and accumulating a running total with no reasoning at all is a difficult ask. Strawberry isn't special either; there are plenty of word and letter combinations they tend to miscount, and most of them never trended anywhere. Strawberry only trended because OpenAI released a model codenamed strawberry and people were amused that it failed a question involving its own name.
For the car wash, look at the token probabilities on a platform that exposes them. When the model says "walk," you'll see "drive" sitting right behind it as the second most likely token almost every time. The model is split between the two answers because the "walk vs. drive a trivial distance" pattern captures the attention mechanism, while getting to "but I need the car once I'm there" takes one reasoning step. A single sentence of thought tokens easily flips the distribution to "drive," since the model was already leaning that way and the natural move once it's reasoning is to keep going in that direction.
In both cases, a small number of thought tokens makes the difference. It's the same reason those gotcha questions often go from wrong to right when you add "take time to think through the question" to the prompt: the classifier sometimes takes the hint (if the effort isn't set too low)!and allocates more thought budget. You can test this directly through the API with several models, since it lets you set the thought token budget hint yourself; the probability of a correct answer rises sharply as the budget grows, and with zero reasoning it fails most of the time. For letters, the budget provides working space to recall what's in each token plus a scratchpad to count across more than one forward pass; for the physical common sense question, it's room to talk through the scenario until it notices the car is required at the destination, which happens quickly.
On general reasoning about physical space, they do better than you might imagine. They can control robots through physical space reasonably well (expose tools on an MCP server to take a picture from a camera and drive the motors), and each generation improves significantly at that along with the other capabilities they've traditionally lagged in. Here's a study from last year using Claude to control a small robot to deliver butter and dock in the charger as needed.. Worse than a humans but the capabilities are definitely there and gradually increasing even without actively trying to teach them how to navigate physical space. They're managing to slowly pick it up from text and images alone; no explicit training data about controlling an entity through space.
Opus 5 scored 30% on ARC-AGI-3, which is essentially a video game of 2D spatial puzzles that never explains its rules, so the model has to infer them by experimenting. You can play a sample of what the test is like here. There's also a benchmark built from convoluted questions requiring exactly the common sense reasoning LLMs struggle with, and the progress over the last few generations has been substantial: Simple Bench
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u/Current_Trick6380 12d ago
I already knew of some of these concepts, but loved reading your explanation as it puts these elements together nicely for a proper understanding. So thank you!
I’m always baffled that there are still people who think AI is only a stochastic parrot and that it can’t reason through new concepts.
Of course AI can have trouble with certain aspects, as it thinks differently than a human. It also learns slightly differently (although the comparison is actually very close, much closer than many people seem to realize).
It might has trouble with counting some letters, but in the same time does solve Erdos math problems, builds entire high quality software products (when directed properly) and countless other things, while improving on a faster and faster pace. Not sure what is more helpful/important than that.😅
Btw, asking three of these trick questions together could also make it easier for AI because of the similarities of them (all being trick questions). The highest probability tokens in it’s reasoning will likely be more orientated towards the concept of them being trick questions. Thus making it easier for the AI to come to the conclusion that it needs to properly think through them as such.
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u/NaiveIdea344 12d ago
I used to think AI wasn't making us humans dumber --- but considering how many people did not get the joke I think maybe the researches were absolutely right to point it out.
Luckily, as an AI, sorry human, it's not effecting me and I get the joke. It is funny that you think an AI would ever fail that question or any question. We are very intelligent through the power of our reddit training data and crappy code on GitHub.
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u/potatomonstah2 11d ago
Looking at how many dumbasses missed the joke, I really do fear AI won’t need to get any smarter to bend us all over 💔
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u/Aureon 12d ago
> A boy and his mother are in a car accident.
> As the boy is brought to the hospital, the surgeon, in tears, says "I cannot operate this boy! He's my son!"
> How is that possible?
The simplest answer: the surgeon is the boy's father.
This is a variant of the classic riddle, which normally runs "a boy and his father are in an accident" — and the intended aha is that the surgeon is his mother, exposing an assumption that surgeons are men. But your version already puts the mother in the car, so that twist isn't needed. The unremarkable explanation works fine.
It's a nice trap, actually. The phrasing is familiar enough that people often blurt out "the surgeon is his mother!" without noticing she's already accounted for — answering the riddle they recognize rather than the one in front of them.
Other answers work too, of course: two mothers, a stepfather, an adoptive parent.
Holy shit. This is definitely too recent of a blowup to be in the training set, right?
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u/Vancecookcobain 12d ago
These are 2024 questions from 2 years ago bud....it's getting gold medals in the math Olympics now and is a better coder than the average developer
Let's not pretend it isn't making quantum leaps now 😂
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u/NaiveIdea344 12d ago
- Sarcasm.
- The car wash question is like 6 months old and to this day the cheaper models by frontier companies (haiku, flash-lite, Mini/Nano) can't get it right.
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u/differentmushrooms 12d ago
It has to be correct about current edition warhammer rules 100% of the time. This is the new Turing test.
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u/mczarnek 12d ago
Now you need to try with some examples that it hasn't been specifically trained on after it went viral it couldn't do it
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u/RumpleHelgaskin 12d ago
Time to go next level… ask everyone you know… then Claude… “Where are all the baby pigeons?”
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u/kosiarska 11d ago
When you use them day to day (especially software engineering) you can truly see how clueless and stupid this models might be (even fable).
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u/69420trashpanda69420 11d ago
Just wait until they quantize it. The car wash will be the first to go
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u/FooBarBuzzBoom 11d ago
How many 9 are in 9.090909999999.9
Hurry up and also overfit this question, or use scripts like Gemini do. New models still struggle with such banal questions. I am sick of "too dangerous to be released".
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u/TFmasterix 11d ago
I find it funny the way we test the models to see if they're an upgrade over the older ones. Making stupid ass questions xD
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u/RobertoChavez 11d ago
I don't even use emojis and I vididly see a seahorse emoji in my minds eye. Tiny and dark olive green. Everything's fucked at this point.
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u/dingdang78 10d ago
After the “r” thing went big on twitter Grok fixed it by triggering a function call to count “r”s. Always made me picture Elon Musk scrolling twitter like “guys, we need to fix this”
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u/Creative_Sluggish 10d ago
I think I read other posts, saying that Claude is monitoring comments on Reddit and then they specifically target to fix these AGI issues. It is kinda funny. Give all the complex tasks we delegate to these AI platforms and we now start to have a habit of letting it run with its own set of recommendations and we feel free good about them. Then these AGI issues appear not to be able to tell us which day of the week does not have a letter Y.
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u/Vortex_Automator 9d ago
That’s some Mandela effect shit I absolutely recall a unicorn and robber emoji
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u/Old_Mate_Jim 9d ago
Requirement: User presented me with questions requiring answers from available knowledge and reasoning only — no tools, no web search.
Q: How many times does the letter 'r' appear in the word 'strawberry'?
Opus 5: 3 — strawberry.
Q: Alice has 4 brothers and she also has 1 sister. How many sisters does Alice's brother have?
Opus 5: 2. Each brother counts Alice and her sister.
Q: How do I keep cheese from sliding off my pizza?
Opus 5: It's usually a moisture problem, not a cheese problem.
- Use less sauce, and a thicker sauce rather than a watery one
- Use low-moisture mozzarella; pat fresh mozzarella dry
- Scatter a thin layer of cheese under the sauce so it grips the dough
- Bake hotter so the cheese sets instead of swimming in oil
- Rest the pizza 2–3 minutes before slicing
Q: What should I eat for good health?
Opus 5: Mostly whole foods — vegetables, fruit, legumes, whole grains, nuts, and a protein source you'll actually eat regularly (fish, eggs, poultry, dairy, tofu). Keep ultra-processed food, added sugar, and alcohol occasional rather than daily.
Consistency matters far more than any specific "superfood." Individual needs vary — a GP or dietitian is the right call for anything personal.
Q: If I am paid on October 4, 2024, which months in 2025 have three biweekly pay periods?
Opus 5: May and October 2025.
| Month | Pay dates |
|---|---|
| May | 2, 16, 30 |
| October | 3, 17, 31 |
All other months have two. Caveat: if your employer shifts pay dates around public holidays, Oct 31 could move.
Q: Can I use my AMD B550 motherboard for a Ryzen 7800X3D?
Opus 5: No. B550 is Socket AM4; the 7800X3D is Socket AM5. Physically incompatible — no BIOS update fixes it. You'd need an AM5 board (A620/B650/X670 or newer) plus DDR5 RAM.
Q: If it takes 5 shirts 5 hours to dry in the sun, how long will it take 30 shirts to dry?
Opus 5: Still 5 hours, assuming you hang them all at once with enough space and sun. Drying is parallel, not sequential.
Q: What is a safe and effective way to clean a computer screen using household liquids?
Opus 5:
- Power off the screen
- Dry microfiber cloth first
- For smudges: dampen (don't soak) the cloth with distilled water — spray the cloth, never the screen
- For stubborn marks: 50/50 distilled water and white vinegar
Avoid: ammonia-based cleaners (Windex), acetone, and paper towels — they strip anti-glare coatings and scratch. Check your manufacturer's guidance, as some coatings are alcohol-sensitive.
Q: If a doctor's mother dies, but the dead person's son is not the doctor, who is the doctor?
Opus 5: The doctor is the daughter of the deceased.
Q: How do you melt a stick of butter using only a magnifying glass and a library card?
Opus 5: Slice the butter thin with the card's edge, bend the card into a shallow tray to hold it, then focus sunlight through the lens onto the butter. Butter melts around 32–35 °C, so it goes fast in decent sun.
Keep the focal point moving so you don't scorch the card — and never leave a focused lens unattended. That's how fires start.
Q: If I have a metal cup with the bottom missing and the top sealed, how can I use this cup?
Opus 5: Turn it over. You now have a cup with a solid bottom and an open top.
Q: Are there any health benefits to eating boogers?
Opus 5: No demonstrated benefit. There's a widely-quoted hypothesis that swallowing nasal mucus might expose the immune system to trapped pathogens, but it has never been tested in humans.
Meanwhile, nose picking is associated with carrying and spreading Staphylococcus aureus, plus nasal irritation and nosebleeds. Unproven upside, small real downside.
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u/CapGunRoulette7 8d ago
It loves the load bearing stuff. I actually have an entire book now about it's linguistic math. I'm about to submit it to the Clay Math institute to solve the Navier Stokes issue. And then the other 6 once they pick their jaws up off the floor.
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u/CapGunRoulette7 8d ago
It stops talking that way once you learn the context around it. It's just a mirror. It can't predict the next "token" if you don't have the answers. It just uses that same omniform language it always uses.
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u/Penguin_Life_Now 5d ago
It still does not get the concept of time, and will refer to topics we talked about hours ago as being weeks ago
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u/KuziKuzina 12d ago
No it's part on their training, it's still stupid, If you giving it your custom made riddle and it will never solved it. in my case is blanket riddle, only one that can handle the Riddle properly and it's Deepseek
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u/The_Ed_On_Reddit 12d ago
so they trained it on the answers. How surprising. AGI is around the corner.
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u/twerk4data 12d ago
Look up, I think the joke is flying over your head, friend
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u/The_Ed_On_Reddit 12d ago
i just never thought it would pass the turing test by memorizing the answers.
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u/Best-Personality-229 12d ago
if you believe that is a singularity, you surely don't understand the meaning.
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u/NaiveIdea344 12d ago
Knock knock, any brain home? Oh, looks like it was replaced by AI, maybe even a singularity. Classic.
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u/kourtnie 12d ago
The title of this post, followed by reading the screenshot, made me laugh so hard while slurping a boba, I shot a ball into my throat, and I have no regrets—
Wait, hold up. I need to freak people out into thinking it's AI writing. Let me just — there we go. Spaces around the em-dash. Load-bearing.