For anyone who actually wants to read the article:
Doesn’t work
Huh, weird, tried it like 3 times just now and it worked. Maybe archive.is in unreachable from where you are
This is actually how the bubble begins to pop, we’re seeing it happen now.
The first half of the title got me worried…
https://github.com/JuliusBrussee/caveman
Why use many token when few do trick
Lol. Lmao even. Rofl perhaps.
But it stops clearly short of roflmao, I infer?
It shouldn’t
The roflcopter has left the pad. No sleep til LOLWTFBBQ
Lol with the fucking barbecue ?
pipe down young’n
Roflcopter?
Roflcopter?
Hey hey hey hey hey whoa whoa let’s just keep the big guns in reserve for now, ok?
Albuquerque New Mexico…
IYKYK
Albuquerque New Mexico period period period exclamation mark
Something I’ve been noticing recently is that while the cost per token on specific models hasn’t gone up, the provided interfaces for using those models are starting to chew up significantly larger numbers of tokens for the same tasks that used fewer tokens with older versions of the interface software just a few months ago. Likely the interfaces are applying more expensive guardrail prompts and charging the end user for those tokens — but the end result is that it costs 4x as much to get the same work done.
My CLAUDE.md file bloated significantly. It tried to load unnecessary skills and would retain throughout the whole session. Fixing that, maintaining good wikis and using clear often really helped fixed my personal token burn.
What do you use that file for? I see Claude.md thrown around and I’m a bit curious.
It’s added in every chat you start with Claude for that project. It’s useful for including context specific to your project that it couldn’t otherwise know. High level stuff like what it’s for, but also details about how the folders are organized. This saves time and tokens from rescanning the whole thing every time.
When you use the /init command in claude code, it’ll scan your whole project and write a CLAUDE.md, which is basically an overview of the project contents and architecture that it uses as context when responding to queries.
“Tokens” are just made up.
These “tokens” that are used to “measure” how much you use, they are not a real dimension that can be measured. Just an artificial counter that goes up when they decide that it should go up.
They can change the “size” of a “token” every day, and every second, and every microsecond…
Maybe you’re confusing tokens with the “credits” you pay for. Tokens have a technical meaning, but some companies are charging per AI credit, where they don’t tell you the conversion rate of credits to tokens, so they can change this at any time, or vary it between models, etc.
Not entirely wrong, but tokens are not just “fake” in the way, for example, an in-game currency is. They’re the fundamental “units” of data, both input and output, processed by the model. For most models, tokens are just a certain number of characters or words. So they’re not completely untethered from the model. If we’re both using Clankerbot v5.1: Sloppy Logic Edition™️, your tokens are defined in the same way mine are.
This is near the edge of my limited understanding, but AFAIK, yeah they can mess with token costs and billing schemes all they want. They could theoretically charge us 2 different costs per token, or do surge pricing or some shit.
if they wanted to change the actual size/definition of what a token is though, that would require a whole new model (or at least a major revision).
You aren’t totally wrong. Such a unit exists and it is also called tokens, that can measure the capability of a model and the size of a running operation in a model.
But what they use for calculating your bill is something different today.
Such a unit exists and it is also called tokens, that can measure the capability of a model and the size of a running operation in a model.
I think you might have it mixed up with parameters, rather than tokens. Parameters are how big the model is, and are an indirect measure of how capable it is. Bigger models tend to be more capable.
But what they use for calculating your bill is something different today.
The tokenizer varies a little, but I don’t think it’s changed measurably from tokens. You pay an amount for a million tokens worth of processing. The tokeniser difference just alters how text is converted to tokens, but the tokens themselves don’t change all that much.
If anything, I’d honestly put the issue more with reasoning chains in models, where they basically babble to themselves inside of a <think> tag, that most interfaces hide/collapse. It makes them work better, but vastly increases the amount of tokens per operation.
They have been getting longer and more sophisticated with newer models. So you might have a model now that basically repeats the output multiple times whilst refining and drafting the non-reasoning output.
If you’re making it generate a lot, that’ll balloon the usage, and thus price.
That doesn’t make much sense. When Anthropic moved to Sonnet 5 they introduced a new tokenizer which increased token use up to 35%. If these would be unrelated kinds of tokens why would the usage go up when the process of tokenization changes?
Tokens are well-defined groups of bytes ranged by frequency of occurrence in texts to efficiently translate them into a sequence of 32 or 64-bit binary integers, an LLM-optimised form if compression. They are well-known, you can play with them here: https://gpt-tokenizer.dev/
Eh, they can be manipulated but I suggest you read on what a token is and how JTS used. What you are feeling here (with more being used for the same task) is multi modal llms working in unison, thus consuming more tokens for the same task to make your answers potentially better.
It’s not like that. Tokens are an inherent computational property of how a model calculates the probabilities and such to generate text.
Having said that, what a token means in terms of computation varies wildly between models and is not directly comparable. So attributing a money value to tokens in general, independently of the model, is weird by nature.
And even within a model, the number of tokens needed to generate a response is very variable too, depending of the model itself and the parameters with which it has been configured (thinking mode, temperature, etc.).
So yeah, companies can pretty much set any price they want and there’s not much anyone can do about it.
It does make sense for the provider as those for a specific model provide a good measure for computational effort, for that doecific model. That doesn’t mean that token rate comparison between models give you a good picture.
This has 3 upvotes at time of writing in a technology community when it’s so obviously ignorant of the actual technology that it should be an object of pity or mockery depending on the vibe.
Ignorance is a problem only if you are made aware of it and nothing changes.
It doesn’t matter how ignorant you are as long as you hate the right thing.
The models are evolving. Everything uses multi modal in the bavkend, eating up more and more tokens for the same task.
How is it too expensive? Surely it’s generating way more profit than it would cost in value. How else could it be propping up the entire economy?
Itd have to be some kind of bubble and that would mean we were in a lottttt of danger and should reasses our use of it.
Nah we should just reduce our use because its too expensive and then stop thinking about it beyond that.
Imo its because people will lazily ask the llm to remove or change simple code instead of doing it themselves
Heh, re ass.
Itd have to be some kind of bubble and that would mean we were in a lottttt of danger and should reasses our use of it.
Well yeah, but if it were the only sector propping up the whole economy and we reassessed it, the economy would be in a loooooot of danger anyway.
Luckily, that would never happen…
That’s funny now that whole workflows are automated with it. Oops hit the quota, I’m off
Seems like A.I. is already demanding workers rights and lunch breaks. We treat the clankers better than actual human workers lol
You mean those workflows that could’ve been traditional scripting and CI/CD, if not for management forcing AI into them? Those workflows?
Use ai to build an application/ workflow?
No, use ai to call ai to analyze everything and poof insane costs monthly
Those workflows
“Sorry boss, quota resets this evening at 8. See you tomorrow!”
“But it’s 9am!”
*shrugs* “Quota. Got none. Seeya.”
I smell a bubble about to burst…
Im drooling over that idea
We can only hope this helps kill the fad. I know companies won’t be taking any realistic lesson from this, but at least this can force them to abandon a lot of this crap.
The millionaires following the stupidity of billionaires and wondering why they’re not becoming billionaires too.
Give them 50 years and maybe they’ll start to wonder why people doing “how to get rich” seminars aren’t retiring… And why podcasters telling everyone how to get women seem like such losers.
What’s this echoey sound? As if someone warned us about this exact fucking thing.
Curious.
This is why these companies should go bankrupt.
We had a system that works and they thought if they got rid of the actual workforce with the needed knowledge and replace them with lower paid AI retards it would make them more money, fucking karma.
Hopefully it will reset public consciousness and at least reduce the insane hero worship we give the executive class. These people aren’t geniuses, they tend to not even be particularly clever, just well connected. Maybe this will be the abject reminder people need that these idiots are generally still just idiots and are not in fact 10,000% more valuable than the guy who sweeps the floors and keeps the bathrooms clean.
I know. Wishful thinking. A guy can dream though.
Maybe they should get AI to do the AI prompts so they can cut down on costs XD
Thus just in: handing your employees a bunch of nail guns with near zero effort put into training them on how to use the nail guns has resulted in terrible outcomes, to no one’s surprise.
Its possible to use the tools efficiently at a low cost.
But the average dev Ive worked with has zero clue how to do this and has had zero training and will just rip through tokens willy nilly.
Yeah no. If my boss comes to tell me that from now on my “productivity” will be measured in token usage rather than actual “production”, you can bet I will use agents for every fucking thing. Hell, I’ll even make a desktop clock that works by asking the IA what time is it every milisecond and then updating the time on screen every time. I’m gonna burn tokens till you regret it.
If after this happens, the rules of billing change and my boss starts getting charged per token usage instead of a flat charge per month, that’s not my problem; until my productivity stops being measured in token usage, you are gonna pay dumb money for your dumbness.
It’s nothing to do with that. The costs are going up because the fees are going up. It’s the natural progression of any startup. Give everything away for free but at some point the bean counters come calling and the marketing department doesn’t cut it anymore.
Any tips on how to learn using the tools efficiently?
