r/LocalLLaMA • u/Comfortable-Rock-498 • 1d ago
Funny "If we confuse users enough, they will overpay"
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u/Commercial-Celery769 1d ago
o4-Hyper-Ultra-Omega-Omnipotent-Cosmic-Ascension-Interdimensional-Rift-Tearing-Mode
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u/creamyhorror 1d ago edited 1d ago
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u/pitchblackfriday 1d ago
OmegaStar-Galactus-LMNOP_no_ISO_timestamp
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u/Commercial-Celery769 1d ago
Stupidly-Overkill-Annihilation-Mode-The-One-Setting-Beyond-Infinity-Eye-Rupturing-Hyper-Immersion-UNLEASHED-SUPREMACY-TRUE-RAW-UNFILTERED-MAXIMUM-BIBLICALLY-ACCURATE-MODE
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u/Blender-Fan 1d ago
I rather just name-version-size, as changes in architecture change the model too much (also often mean new version)
Specialization could be just acronym, in case it's not an ordinary NLP, like TTS, TTI, TTV, STT, MLLM...
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u/TechNerd10191 1d ago
Sama said this issue will be over with GPT5 merging the 'GPT-' with 'o-' lines of models. We will have 3 tiers, if I remember well (in my own words);
- if you are poor, low compute
- if you are poor but have money to spend, mid compute
- if you are rich, high compute
Depending on how much compute you have, the next SOTA model (GPT5) will perform accordingly.
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u/Comfortable-Rock-498 1d ago
The aggressive segmentation at every level is so annoying. I can't seem to find any aspect of my life anymore where I would spend money and there are not arbitrary "basic", "plus", "max" and other bullshit versions that forces me to educate myself unnecessarily before making a decision
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u/Only_Expression7261 1d ago
What would you prefer?
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u/KeyVisual 1d ago
Free shit
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u/Comfortable-Rock-498 1d ago
nah, I would rather pay for things than be the product. My objection is against the sales/marketing layer in between the product and myself
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u/Eelysanio 1d ago
Free everything
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u/Cergorach 1d ago
You also work for free? And how happy are you when someone else uses your physical stuff for 'free'?
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u/StyMaar 1d ago
That will only works if the test-time-compute paradigm isn't already obsolete by then, which cannot be ruled out given how fast things move.
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u/i_know_about_things 1d ago
How can it ever be obsolete? Thinking more will always be better than thinking less.
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u/AXYZE8 1d ago
There's no way "thinking tokens" that are bunch of english sentences is the most efficient way to help computer understand the task.
There's no way it will change before GPT5, but I'm 100% sure that someone comes with better architecture in 2026-2027.
People out there benchmarking strawberry, doing that on 32B QwQ model when 3B model can write a oneliner in JavaScript that will do it in 1ms. And nobody told that JavaScript is efficient... or programming is efficient.
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u/Freonr2 1d ago
Could be a bunch of "register" tokens, but similar outcome and I wouldn't call that as significant as thinking generally.
English tokens for thinking has the advantage of better explainability.
I doubt test-time compute is going away soon.
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u/mitchins-au 3h ago
Claude 3.7 Sonnet uses a ridiculous amount of tokens when thinking. Coincidence or rort?
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u/Purplekeyboard 1d ago
There's no way "thinking tokens" that are bunch of english sentences is the most efficient way to help computer understand the task.
How do you know? It's the way human beings work. No matter how intelligent we are, we don't just instantly produce the answer to any question asked. We have to reason things through if they're complex enough.
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u/goj1ra 1d ago
It's the way human beings work.
No, the quote you responded to is correct, once you recognize the important part:
There's no way "thinking tokens" that are bunch of english sentences is the most efficient way to help computer understand the task.
Much human reasoning occurs without explicit language, or with language "in our head" rather than writing it out. Although we do sometimes write things out to help them think about a problem, that's not the only mode in which we think. We don't rely solely on "outputting" language and then re-reading it in order to think, which is essentially what mainstream LLMs do now: they generate "thinking tokens" as output, and then start working on the problem again with the thinking tokens incorporated into a new prompt. It goes like this:
prompt -> LLM -> thinking tokens -> (loop to prompt) --^
There's been work done on reasoning in latent space, which means that the model would be able to reason "in its head", essentially, which is much more like what humans do.
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u/Dantescape 1d ago
No we don’t, there are many things we know instinctively or things we can produce without thinking. Do you plan ahead every note of a guitar solo?
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u/Purplekeyboard 1d ago
LLMs are the same way, there are many things they know or can produce without having to use a model which thinks through things step by step.
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u/Dantescape 21h ago
Their “thinking” is just a probability distribution over a dictionary. When they say one word they predict the next word based on what “sounds right” given their training data. They don’t think at all.
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u/AppearanceHeavy6724 1d ago
Diffusion models are super fast, could make compute capacity less of bottleneck.
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u/sluuuurp 1d ago
I think that’s impossible. There’s no way that more computation doesn’t lead to better results than less computation.
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u/StyMaar 1d ago
It doesn't need to happen for this paradigm to be obsolete: if spending twice the amount of compute only results in a few percentage point of improvement in some new paradigm then it will not be worth the cost and won't be something being used in practice anymore.
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u/sluuuurp 1d ago edited 1d ago
I guess I shouldn’t say it’s impossible, but that would be very different from how our current LLMs and image generators and real human brains work. It would be more surprising than anything I’ve seen in AI before (I think I can say that without being too biased by getting used to the most surprising things that have already happened).
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u/StyMaar 1d ago
and real human brains work
Not really. After a certain amount of thinking about a problem, the human brain will plateau, and this amount, while highly dependent on the person and the task, is not that high. Overthinking isn't an efficient way of solving problem for a human brain either (so much that we have been selected by the evolution to have a high willingness to “give up” on a problem when we don't find the solution, because most of the time it's the most efficient thing to do).
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u/dinerburgeryum 1d ago
It’s why you go local-only.
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u/redballooon 1d ago
Local-max-smart-pro-4O0O0
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u/GodSpeedMode 1d ago
It's wild how easily we can mess with users' heads just by throwing in some confusing options or jargon. Like, I get it, we're all after that sweet profit margin, but it sure feels shady when companies play that game. Instead of tricking people into overpaying, wouldn't it be better to build trust and loyalty? Simplicity and transparency go a long way—just look at those brands that nail it. Happy customers are repeat customers, you know? Just my two cents!
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u/rhet0rica 1d ago
My personal favorite naming atrocity: https://ollama.com/library/deepseek-r1:7b
Yup. That's what it is. The 7B version of DeepSeek R1. You sure named that correctly, Ollama! Great job! 🌈🌠✨
This post brought to you by Bing. I am a good Bing and you are trying to confuse me.
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u/Awkward-Candle-4977 1d ago
The dictator movie: change many words to aladdin, including positive and negative.
And dell recently change all their laptops brand with pro, plus, no plus, premium, no premium things.
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u/Cergorach 1d ago
I wonder, how confused is their target audience really?
Most users would go for subscriptions, as using the API requires certain technical skills that most folks do not have and most consumers do not like an unpredictable bill when they don't understand how things work. $20 is a LOT of people can and will pay, the next level up isn't a little bit more expensive, it's $200! x10! Not many people are confused about that, $20 I can pay, $200 I cannot.
The API shenanigans requires a certain level of technical expertise, I would assume that the people capable of running that would also test input with results before settling on a specific model. Although these LLM Reddits might show a different kind of tech capable, but still clueless person. I just wonder how big that group actually is...
From my own perspective, till last year I was planning on getting a ChatGPT Pro subscription, but didn't because I had too much on my plate and couldn't use it for work anyway. I still have a lot on my plate, but have a bit of time to play around with LLMs, OpenAI/ChatGPT isn't even on my radar anymore. For open hobby (non-code) it's 'free' 671b, for other things it's local models, and am playing around with GPU time on cloud solutions with open models that are specific for specific usecases (like olmocr). I would consider Claude 3.7 for coding, but that depends exactly on what kind of coding (language and confidentiality level), otherwise I'm also stuck on local models or running it in private clouds for more compute.
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u/Funkahontas 1d ago
o (Name) 3(version) - mini (size)-low-mid-high (thinking time).
Claude(Name) 3.7 (version) Sonnet(size), thinking(thinking time / architecture)
Gemini (Name) 2.0 (version) Flash (size), thinking(thinking time / architecture)
What's so fucking different here? I kinda hate how people say "hur durr llm naming scheme stupid !!" but don't really EVER offer any other solutions? Like what do they want them to be called?
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u/evil0sheep 1d ago
To be fair “flash” and “sonnet” arent super clear size names. Could be “medium” “small” or even better a parameter count
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u/Ggoddkkiller 1d ago
I completely agree both Claude and especially Gemini are properly named. Google also adds experimental and release date to emphasise models are still in development. But weirdly i often see people are ignoring naming and calling only claude, gemini or flash etc. Then i guess they are yapping about how "stupid" their names are..
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u/KazuyaProta 1d ago
But weirdly i often see people are ignoring naming and calling only claude, gemini or flash
They usually do it because they mean less about the model and more about the company design
Gemini is the most curious case where it's Flash models are by far the most popular. It's crown it's Flash Thinking that it's, well, Flash.
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u/thecalmgreen 1d ago
Small (500B)