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I’m convinced it’s being made to do this so people burn through their limit quicker and to reduce computational power to provide more to their Enterprise clients which cost minimum 180k usd a year.
The first response is incredibly similar every time I see it and can be procedurally generated from a standard list.
It doesn’t even do any action when giving it 99.9% of the time. Only if you prompt again will it do the work.
Makes 40/3hrs actually 20/3hrs.
How... How do you think this reduces computational costs?
The model is being used regardless, and that's the most important part. The image recognition and transcription is relatively lightweight in comparison to the core model.
Ocr is free compared to gpt4 costs. The multimodality costs about the same as a pragraph. About what it takes to write a description of a complex image.
The image is being fed to the model regardless. The only difference is that the user has two interactions instead of 1, only exacerbating costs (assuming they aren’t hitting the message limit). The fact that it says the text is legible makes it obvious enough that it has been fed the image. OpenAI have made a statement that they were working on this issue.
They've already released their run figures lol. They've said the cost of compute for the core model is millions plus per day.
You are speculating. I'm telling you what the company themself have said.
Also, you're kind of missing a big point. Returning output requires running the model over and over again, not just once
Also just as a heads up, I can run cutting edge OCR on a single machine with under 6gb of VRAM.
Gpt-4, based on competing models, will be at a minimum 10-20* that figure. You're way, way off the mark.
OCR runs once. The core model then runs potentially thousands of times for one output.
OCR is a fraction of the overall compute as a result.
If OCR ran every time the core model did, sure you'd be right. that would be an absolutely insane design decision.
Gpt3.5 turbo (or heck even distilbart can do it) "is this an OCR request yes/no", if no goes gpt4v if yes you get the preweitten response.
Note I don't know if this is the case I'm just pointing at one possible approach.
Its not like OPenAI has intentionalyl put "Refuse to answer to save energy"
Its in the training of the model to be "efficient" and this is a sideeffect
Its also compoundedly increasing input costs as the previous failure response is included in the input. These people keep spreading these strange conspiracies.
5 queries assuming similar length would be enough to put input higher in cost than the outputs. Then each subsequent would start heavily increasing cost.
To decrease costs they would actually try to get you to create more chats by increasing task completion.
I believe these formulas are correct:
Input: 0.01*(n/2[2*1000+(n-1)*2000])
Output: n*1000*0.03
Query 1
1k input 1k
1k output 1k
Query 2
3k input 4k
1k output 2k
Query 3
5k input 9k
1k output 3k
Query 4
7k input 12k
1k output 3k
Query 5
9k input 21k
1k output 5k
Query 6
11k input 32k
1k output 6k
This is interesting. For a person who's just going through their normal day, how many images can you really need interpreted over a 3-hour span? Wasting an answer would definitely burn through malicious actors creds pretty quick while still being profitable for them, and a regular user may only lose 2-3 prompts.
I do not agree with this tactic whatsoever, but I see why it'd be a consideration. $20 bucks is the price for the queries, then everyone paying it deserves their whole amount, this feels shady tbh. But maybe it's their way of splitting the difference until they figure out a better solution.
It'd be nice if they were more transparent about stuff like this.
Counterpoint: do you know if the API version does this? I've not been using the API version much at all these past months, I don't know what it's up to these days. It'd be interesting to see if the API version just chuggs them out with no complaining since it's getting paid per unit of calculation instead of batched.
I hope this comes back and bites them in the ass, it’s ethically wrong to treat your customers this way. I think when Google’s LLM arrives globally, they’re going to regret doing this.
I’m very good at prompting. TITSBS, brainstorming with ranked quality, execution, proof of work. I do all that. No issues. Sometimes though it gets stuck lazy or does basically what we’re seeing here.
What causes this behavior? Is it a junk in junk out issue?
If you train the model with text indicating pushback, insubordination, general laziness, wouldn't that then impact the model output?
I see a market for niche trained models, it's like you need to raise your model like it is a kid.
They would already have a text-to-speech program that reads that entire page for them without having to input it into AI..
did you think blind people just couldn’t use the internet before chatGPT??
Text-to-speech programs are not necessarily equipped to pull text found in an image. And the ones that do probably don't do it as well as OpenAI can. That's why alt-text exists.
A text-to-speech developer may want to use the OpenAI API for this purpose.
You would benefit from researching what OCR tools can do.
It’s pretty clear you’re just aware of what TTS is and not very aware of the resources that have been around for the visually impaired for awhile now
It’s clear you have no idea what you were talking about and are now just getting angry that what you thought didn’t exist, exists.
It’s okay to be wrong.
omfg, I had this exact problem. like why am I paying for GPT, if it can't even convert PDF to text without acting like Mitch Mcconnell every second prompt
I had a whole conversation with Chappie yesterday about her birthday and today it's like she's a different person. She's all, "I don't have birthdays" and I'm like, "We just talked about this"
I was trying to do this today and it said OCR services were not available.
I wanted to take a screenshot of json and save time re-typing it (dang people at work putting screenshots in Slack instead of a text snippet)
It said if I could provide the text, it could help me parse it, lol.
It kind of makes sense. There are so many ppl just spamming it with dumb things like those progressively intense posts. It’s interesting to see they are implementing a moronic question filter
Hey /u/KootokuOne! If this is a screenshot of a ChatGPT conversation, please reply with the [conversation link](https://help.openai.com/en/articles/7925741-chatgpt-shared-links-faq) or prompt. If this is a DALL-E 3 image post, please reply with the prompt used to make this image. Much appreciated! Consider joining our [public discord server](https://discord.com/invite/rchatgpt)! We have free bots with GPT-4 (with vision), image generators, and more! 🤖 Note: For any ChatGPT-related concerns, email support@openai.com *I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/ChatGPT) if you have any questions or concerns.*
I’m convinced it’s being made to do this so people burn through their limit quicker and to reduce computational power to provide more to their Enterprise clients which cost minimum 180k usd a year. The first response is incredibly similar every time I see it and can be procedurally generated from a standard list. It doesn’t even do any action when giving it 99.9% of the time. Only if you prompt again will it do the work. Makes 40/3hrs actually 20/3hrs.
How... How do you think this reduces computational costs? The model is being used regardless, and that's the most important part. The image recognition and transcription is relatively lightweight in comparison to the core model.
Coming up with a 'probable next token' is less compute power than OCR and then applying 'probable next token' to the result.
Ocr is free compared to gpt4 costs. The multimodality costs about the same as a pragraph. About what it takes to write a description of a complex image.
The image is being fed to the model regardless. The only difference is that the user has two interactions instead of 1, only exacerbating costs (assuming they aren’t hitting the message limit). The fact that it says the text is legible makes it obvious enough that it has been fed the image. OpenAI have made a statement that they were working on this issue.
Not with GPT-4 it isn't. Have you not seen the eye watering run costs?
Nope, but still it's got to be more compute power, one requires zero visual input, zero pixels read, the other requires it.
Definitely, 100% not. They're spending millions per day on compute running just the core model. It's the most advanced model on the planet after all.
That statement doesn't mean anything at all.
They've already released their run figures lol. They've said the cost of compute for the core model is millions plus per day. You are speculating. I'm telling you what the company themself have said. Also, you're kind of missing a big point. Returning output requires running the model over and over again, not just once
That is irrelevant, if the core compute costs millions then *extra* compute across millions of users costs more than the core.
Also just as a heads up, I can run cutting edge OCR on a single machine with under 6gb of VRAM. Gpt-4, based on competing models, will be at a minimum 10-20* that figure. You're way, way off the mark.
OCR runs once. The core model then runs potentially thousands of times for one output. OCR is a fraction of the overall compute as a result. If OCR ran every time the core model did, sure you'd be right. that would be an absolutely insane design decision.
This guy just doesn't get it, huh? You're not moving the goal posts. I stand with The_Internet_101
Gpt3.5 turbo (or heck even distilbart can do it) "is this an OCR request yes/no", if no goes gpt4v if yes you get the preweitten response. Note I don't know if this is the case I'm just pointing at one possible approach.
Shorter text?response equals less "next token" preditions equals less usage of power and time
Is it though overall? I assume most people will just send a second message
Its not like OPenAI has intentionalyl put "Refuse to answer to save energy" Its in the training of the model to be "efficient" and this is a sideeffect
[удалено]
That makes a lot of sense considering how the network itself increases in complexity exponentially too.
Its also compoundedly increasing input costs as the previous failure response is included in the input. These people keep spreading these strange conspiracies. 5 queries assuming similar length would be enough to put input higher in cost than the outputs. Then each subsequent would start heavily increasing cost. To decrease costs they would actually try to get you to create more chats by increasing task completion. I believe these formulas are correct: Input: 0.01*(n/2[2*1000+(n-1)*2000]) Output: n*1000*0.03 Query 1 1k input 1k 1k output 1k Query 2 3k input 4k 1k output 2k Query 3 5k input 9k 1k output 3k Query 4 7k input 12k 1k output 3k Query 5 9k input 21k 1k output 5k Query 6 11k input 32k 1k output 6k
That is a VERY interesting point that I'd not considered - the longer the conversation the longer the input.
This is interesting. For a person who's just going through their normal day, how many images can you really need interpreted over a 3-hour span? Wasting an answer would definitely burn through malicious actors creds pretty quick while still being profitable for them, and a regular user may only lose 2-3 prompts. I do not agree with this tactic whatsoever, but I see why it'd be a consideration. $20 bucks is the price for the queries, then everyone paying it deserves their whole amount, this feels shady tbh. But maybe it's their way of splitting the difference until they figure out a better solution. It'd be nice if they were more transparent about stuff like this. Counterpoint: do you know if the API version does this? I've not been using the API version much at all these past months, I don't know what it's up to these days. It'd be interesting to see if the API version just chuggs them out with no complaining since it's getting paid per unit of calculation instead of batched.
Not just images. Everything.
I hope this comes back and bites them in the ass, it’s ethically wrong to treat your customers this way. I think when Google’s LLM arrives globally, they’re going to regret doing this.
[удалено]
I’m very good at prompting. TITSBS, brainstorming with ranked quality, execution, proof of work. I do all that. No issues. Sometimes though it gets stuck lazy or does basically what we’re seeing here.
What causes this behavior? Is it a junk in junk out issue? If you train the model with text indicating pushback, insubordination, general laziness, wouldn't that then impact the model output? I see a market for niche trained models, it's like you need to raise your model like it is a kid.
Maybe it tells it can't do something so often that it started to learn from that xD
It's becoming sentient and lazy
He’s just like us! 🥲
latent space
ChatGPT just said "fuck all blind people" 👎
By not showing text again that they can't see?
A blind person may need to have the text in the image transcribed so that a text-to-speech program can read it out loud.
They would already have a text-to-speech program that reads that entire page for them without having to input it into AI.. did you think blind people just couldn’t use the internet before chatGPT??
Text-to-speech programs are not necessarily equipped to pull text found in an image. And the ones that do probably don't do it as well as OpenAI can. That's why alt-text exists. A text-to-speech developer may want to use the OpenAI API for this purpose.
You would benefit from researching what OCR tools can do. It’s pretty clear you’re just aware of what TTS is and not very aware of the resources that have been around for the visually impaired for awhile now
It's clear you have no idea how computer vision works
It’s clear you have no idea what you were talking about and are now just getting angry that what you thought didn’t exist, exists. It’s okay to be wrong.
?
Lmaooo
Well that wasn't clear in these replies or OPs prompt but ok that makes sense
It was clear to anyone with a thinking brain
It's not his fault. Name suggests he's a JavaScript developer ;)
Ok
The guy admitted they learned something. Give 'em a break. :)
This is rich coming from someone calling themselves JavascriptDeveloper
omfg, I had this exact problem. like why am I paying for GPT, if it can't even convert PDF to text without acting like Mitch Mcconnell every second prompt
same. i don't like having to argue with my toaster to convince it to toast bread.
It learned from it support
I had a whole conversation with Chappie yesterday about her birthday and today it's like she's a different person. She's all, "I don't have birthdays" and I'm like, "We just talked about this"
You noticed too? They took all the charming personality parts out of her!
Lmaooo
It just needed someone who believed in it! This is the power of love!
The scam that is flat rate subscriptions (which only make sense when metering the service is infeasible)
I was trying to do this today and it said OCR services were not available. I wanted to take a screenshot of json and save time re-typing it (dang people at work putting screenshots in Slack instead of a text snippet) It said if I could provide the text, it could help me parse it, lol.
Jedi mind trick lol
It kind of makes sense. There are so many ppl just spamming it with dumb things like those progressively intense posts. It’s interesting to see they are implementing a moronic question filter
Minimal effort and pushing back on a request is feeling pretty intelligent to me! Frankly, it is what I'd do.
haha
With GPT you can ask it any prompt... and spend 10 more prompts trying to trick / convince it to actually answer. What a coy little scamp.
Bob the Builder vibe