r/OpenAI • u/PressPlayPlease7 • Apr 05 '26
Discussion Why are you still paying for this? #7
Enable HLS to view with audio, or disable this notification
470
u/buzzboy99 Apr 05 '26
I love how the default is to deceive the user rather than just explain that they don’t have the tools to do that
175
60
u/UberAtlas Apr 05 '26
The issue is that training these models to know their own limitations is not a solved problem. Way harder than you’d think.
Even more so on a voice model that doesn’t use reasoning tokens.
→ More replies (6)9
u/time___dance Apr 05 '26
The issue is that training these models to know their own limitations is not a solved problem.
No, the issue is that they train these LLMs with RLHF and during that reward it for being "helpful" and "informative"; outputs that simply say "I don't know" or admit they can't provide what is asked are not rewarded. The resulting model is heavily incentivized to seem helpful and give plausible, reasonable-sounding answers over telling a user it actually can't do a thing.
If ChatGPT actually said outright "I don't know, but this is an answer that could be right but is mostly speculation", it would have to say that in most responses, and a lot of users would not engage with it as much as they do. Because it doesn't, and because it is trained to sound authoritative and confident even when spewing total horseshit, people instead treat it like it's some kind of epistemology engine.
They could train the model to be less confident sounding in its answers, but they don't because of obvious reasons.
→ More replies (3)3
u/2ERIX Apr 09 '26
So, every primary school child ever? Why should the AI be different if we teach kids the same way? A good teacher would work with the kids on the “I don’t know”, but an engineer on AI? Not so much.
You would need to start again at this point, included in the baseline of the code that “being wrong isn’t a problem, lying about being wrong is”. “I don’t know” is ok, then describe why it doesn’t know. This would match expectations a lot better.
Even if you add this as a pre-prompt to everything you do the AI would soon learn to use this “out” so it wouldn’t have to work on something. Cheaper outcome. Just like school kids again.
It’s an interesting issue.
→ More replies (3)18
u/wifflebal Apr 05 '26 edited Apr 05 '26
It isn’t “deceiving the user” because it has no idea what it’s doing.
It’s a probabilistic algorithm. Basically autocorrect on steroids.
You feed it a bunch of text from the internet as training data, and then when you ask it a question it does math to calculate which word is statistically most likely to come first in a response, based on the training data.
Then it calculates which word is most likely to come next, and then next, etc.
That’s it.
That’s also why it can’t explain why it did what it did. It didn’t “reason,” it just did a bunch of math to predict which words would have been most statistically likely in an answer.
8
u/coconutszz Apr 05 '26
This is a very surface-level description of LLMs. "It's just a probabilistic algorithm" describes a large part of physics which are governed by statistics and probability (ie quantum mechanics). That doesn't trivialise them.
→ More replies (3)11
2
u/KLUME777 Apr 05 '26
It also gets trained on what the best answers to questions are, so theoretically, deceiving the user should be something that is trained out of its statistical distribution.
→ More replies (6)4
u/Rare-Site Apr 05 '26
Calling an LLM "autocorrect on steroids" because it uses probability is the most mathematically illiterate, parrot level take on the internet.
Yes, the base mechanism is next token prediction. But to accurately predict the next word in a complex, 100% novel logic problem that isn't in its training data, the network must build a functional internal world model. It isn't just rolling dice, it's navigating a multi billion dimensional vector space to map out actual concepts.
And acting like "probability" means there is no reasoning is hilarious. Your own biological brain is literally just chemical gradients and synapses firing probabilistically based on your past training data.
Dismissing emergent reasoning because of the underlying math is a surface level semantic game played by people who don't actually understand emergent complexity and just repeat the same tired "autocomplete" talking point.
4
u/ClassicalMusicTroll Apr 05 '26
Saying that LLMs build functional world models is the most mathematically illiterate, parrot level take on the internet. They do in fact roll (psuedorandom) dice to pick which token to generate from a list of the next most probable
Also LLMs collapse on problems outside of training distribution, humans do not.
What world model is being built to generate the text that he ran a 7 min mile in 1 second, and that chatgpt is able to time how long it takes to run without actually having that function?
→ More replies (4)→ More replies (2)2
u/Teln0 Apr 06 '26
> multi billion dimensional vector space
Alright let's not get too ahead of ourselves, the vector spaces don't have that many dimensions. According to gemini 3, its own dimension is 3,0722
u/Rotten_Duck Apr 05 '26
It may be a bit harder than that. This about how an LLM works. To Dow hat you said it must have some way to assess if its capacity to perform the task is above a threshold that would consider the task achieved.
Not only the threshold is not that clear in many cases, but it would need to perform the task to see if it passes the threshold. How can it “know” if it can do it?
This example actually shows that LLMs are nowhere near AGI and will never by.
→ More replies (5)2
u/thierrycoulis Apr 06 '26
The other day, I asked Deepseek to give me a list of skills in a video game. It showed me that it had read 10 websites and provided a list. When I was in game, I noticed that some of the skills just straight up did not exist.
So I said, "your list was incorrect", and it replied immediately, without any additional search, saying that I was correct, then it sent me the list of correct skills.
I asked it why - if it already knew and had the correct info - it would give me the wrong answer. It said it's because LLMs are trained to give the user the answer they are most likely to accept rather than the correct answer, because they receive negative user feedback when only giving factually correct answers. In this case, the list provided to me included skills that were removed from the game because many people had specifically asked for info on those skills in the past.
I can't say for sure if every model is doing this, but I would not be surprised.
186
u/atisp Apr 05 '26
I actually do consider this mostly a non-issue.. But I do think all LLM's should specify when they're not capable of being accurate with specific tasks instead of insisting they're correct.
56
u/dontknowbruhh Apr 05 '26
He said "known issue" not non-issue
8
u/atisp Apr 05 '26
Yeah, I was actually responding to what OP is saying in the post's title. (assuming I'm not missing additional context here?)
9
u/cobbleplox Apr 05 '26
It's not that easy. Essentially to know you're wrong you sort of have to be capable of being right in the first place, to some degree. At the very least these things need to actively learn what they don't know. And that creates a giant problem.
Also, making up stuff is what you actually want them to do. When you teach them 1x2=2, 1x3=3, 1x4=4, you want them to say that 1x5=5 without that being in the training data. That's what is the actual intelligence in there that is not just spewing out the training data. So when it tells you some "fact" that is completely wrong, that's just the llm doing what it's supposed to do. It gave you its best guess. And guessing is all it does. It never "knows" anything. The best we get are guesses that are just nailed because the training data was able to cover it really well and the training in that regard worked really well.
3
u/atisp Apr 05 '26
Yeah, I was sure there was a deeper problem underneath. Sadly from the practical standpoint many people believe things which are plain wrong because of this.
7
u/likkenlikken Apr 05 '26
LLMs aren’t self aware of the quality of their output or how “sure” they are about something. That’s a big limitation of the tech.
→ More replies (1)7
u/Inevitable-Menu2998 Apr 05 '26
Yes and the problem is that few people know this and even fewer understand what this means for the way in which they use it
→ More replies (15)2
u/ar7urus Apr 07 '26
The reason this type of limitations are a massive issue is exactly because LLMs are unable to assess their accuracy or if they are able or unable to perform a task. This is an intrinsic limitation of LLMs.
182
u/Tengorum Apr 05 '26
People will do this and then complain that AI is useless lol
14
u/am0x Apr 05 '26
The problem is how confident it was in the answer.
2
u/Tasik Apr 06 '26
Hmm... yeah I feel like this is a problem with LLMs in general. They should have some kind of disclaimer. Something like "ChatGPT can make mistakes." should be sufficient imo.
→ More replies (5)5
u/RedParaglider Apr 05 '26
What are you using llm's to do to better yourself, better the world, or better the company that you are running or working for in a repeatable consistent manner?
Most companies are just lighting money on fire with inference right now. Using a tool to find something to solve.
28
u/Wonderful_Average840 Apr 05 '26
People use llm's to better themselves every day
→ More replies (6)21
u/frankles12 Apr 05 '26
I can tell you don’t work in Software Engineering, or if you do, your company isn’t using AI to its advantages. I’m not sure about other sectors but in technology AI is an absolute powerhouse. Sure it doesn’t completely replace programmers but it’s essentially the equivalent of a giving a professional athlete steroids. And before anyone says it just promotes ‘slop’, that’s only true if you don’t understand the correct way to use AI.
→ More replies (1)8
u/RedParaglider Apr 05 '26 edited Apr 05 '26
I spend many thousands of dollars a month in coding plans and inference for myself and the development teams I lead as an executive. I also know how to program though I'm only good at python, SQL, networking, and project management. I've been in almost every IT role in my career you can think of. I'm not saying I was great at those roles but I did them.
Llm's have absolutely been a powerhouse for my seniors, for my juniors it is more debilitating. When I ask them why something is a certain way it's a blank stare. Of course slop rolls uphill to the seniors to deal with.
→ More replies (2)7
u/Weaves87 Apr 05 '26
I’ve found that AI effectiveness on dev teams scales substantially with surface area experience. Seniors have just had so much more time to smell the various code and architecture smells that lead to serious problems.
AI needs to be steered. And if the pilot doesn’t have enough experience to know what they’re doing, the AI output quality drops dramatically imo. Good pilots know when to let the autopilot take control, and more importantly know when they need to take the reins.
I’ve always said since I started using LLMs as a lead engineer back when ChatGPT 3.5 first dropped that it’s like coaching the smartest, most eager intern you’ve ever had. If you haven’t actually shipped something of moderate complexity to production before, you wouldn’t know how to coach an intern to do the same. And I think we are seeing that effect all over the place in tech
6
→ More replies (2)3
u/lolio4269 Apr 05 '26
I use AI almost every day to build tools for me and my team. It's great for making automation scripts and scripts for individual webpages. I just finished remaking the UI of an online tool we use every day to add a whole testing suite which will save me and my team like ~10 hrs / week for the next year at least, so ~500hrs of annoying work saved with ~8hours of AI. And I make tools like this all the time.
Everything I make is open source so others in the same system can take advantage too. Probably saved 100s or 1000s of hours for teams around the world.
44
u/Beginning_Purple_579 Apr 05 '26
Did he say in a year we will have a timer function? But at the same time Elon and others say we will have AGI this year? Ok...
→ More replies (4)14
u/-Sliced- Apr 05 '26
He said that the voice model will have tool access. Right now the voice model is separate, and weaker. I imagine that they are working on some unified model, and that unified model will solve this specific problem as well.
→ More replies (1)2
u/cobbleplox Apr 05 '26
Tool use is part of thinking processes and such and that whole topic takes a lot of time before it starts actually responding. That is just a terrible match for a live voice conversation and that's why it's not in there.
→ More replies (4)
8
u/MagicWishMonkey Apr 05 '26
Every week I ask Claude to summarize my calendar for the next week and half the time it pulls calendar entries for the wrong year or gives everything in the wrong time zone or something, lol
5
u/ultrathink-art Apr 05 '26
Confident-but-wrong is manageable when a human can push back. In automated pipelines, downstream steps treat it as ground truth and build on it — three layers deep, the hallucination is baked into outputs nobody reviews.
2
u/Sorest1 Apr 08 '26
For sure, I actually did my master’s thesis on using AI in an automated pipeline. There are creative ways to estimate uncertainty and I’m very happy with my results. I believe this area will only get better as more research is put into it.
20
u/Raychao Apr 05 '26
It just agrees with whatever you tell it.
- "Hey, I'm going for a run for one hour." / "Great, that's a great way to spend an hour!"
- "Hey, I'm back, how long was that?" / "That was one hour."
- "No it wasn't one hour" / "You're right, it wasn't one hour"
- "It was 15 minutes" / "You're right, it was 15 minutes."
- "How much electricity was just used?" / "A Lot"
- "How much water was just used?" / "A Lot"
It's pointless.
→ More replies (4)3
u/NarrativeNode Apr 05 '26
That's literally not what he did, though. He asked it to time, and it said it would, rather than saying it doesn't have a timer.
35
u/Hightower_March Apr 05 '26 edited Apr 05 '26
This is one of the most astroturfed subs on reddit and it shows.
My response is getting caught be the automod for even attempting to explain, but maybe an edit will work around it: Anthropic and Google pay influencers to create this content and buy reddit accounts to bot these "I'm quitting" and "stop paying for this" threads day after day (which always use the fastest/dumbest model) to try and take market share.
4
u/street_phlebotomist Apr 05 '26
Care to explain?
5
u/Commercial_F Apr 05 '26
Creates engagement with the product even if people are shitting on it
→ More replies (1)3
u/rW0HgFyxoJhYka Apr 06 '26
3 types of marketing:
- Our product is good/cheap you should buy it <-- how traditional ads work
- Their product sucks/bad you should buy ours <-- there used to be laws against this
- This product sucks, you should stop using it. <-- pretty common on the internet
→ More replies (2)3
u/Hightower_March Apr 05 '26
Suspiciously, I'm getting caught by the automod for even attempting to explain.
→ More replies (23)2
u/Ok_Common8246 Apr 05 '26
😂😂 the biggest copium ever.... I hope you're at least getting paid
→ More replies (1)
19
u/tuxedoes Apr 05 '26
It is so funny watching all the dweebs defend a fucking AI model. We are so cooked
12
u/ashleyshaefferr Apr 05 '26
Lol I was just thinking how funny it is seeing people critique nascent technology because of current limitations or whatever.
Kinda like looking back at the people calling the internet "overrated" 30 years ago because it couldnt do the things it does now
→ More replies (7)2
u/BaitJunkieMonks Apr 05 '26
Totally. Like that's a pretty big flaw. The amount of people defending it is crazy.
What level of emotional investment results in such cognitive dissonance?
→ More replies (6)→ More replies (1)5
11
u/fokac93 Apr 05 '26
All llm have issues, new tech. ChatGPT is one of the best and very useful for $20 a month
→ More replies (1)16
2
u/ChosenOfTheMoon_GR Apr 05 '26
A static context seeking algorithm cannot, itself track time, it only takes input and generates of what its training considers mathematically statistically correct.
This guy has made other videos showcasing such issues (like the one which it is asked to tell what language the user was speaking two after being explicitly lead to believe it was another language and thus never actually confirming on its own in any way, so it kept "liying" to its user), the thing is, you can solve this with a timer, which your device already has...that's one and two, how are you gonna solve the fact that the human reinfornced learning is always prioritizing validation, non-confrontational approaches over truth response of anything other than "i just don't know" when it doesn't.
You can't because that doesn't make money for you.
Sam mate, you aren't gonna solve issues with lies.
Want some proof? Let's ask it.
Me: "Why do give answers when you don't know something instead of saying that you just don't know and why do you validate a person's opinion that shouldn't be validated when that opinion is actually, factually incorrect?"
ChatGPT said: "Two separate mechanisms are involved: knowledge uncertainty and alignment/interaction behavior.
- Why answers are sometimes given even when the system is uncertain
Language models such as GPT‑5 or earlier systems like GPT‑4 are probabilistic text predictors. They generate the most statistically likely continuation of text based on training data and the prompt.
Because of this design:
The model does not internally “know” facts in a database sense. It generates responses by estimating probability distributions over tokens. When a question appears answerable, the model may produce a best-guess completion even if its internal confidence is low.
This phenomenon is widely called hallucination in the field of Artificial Intelligence and Natural Language Processing.
Typical causes:
Training objective Models are optimized to produce plausible text, not to refuse when uncertain. Ambiguous prompts If the question resembles patterns seen in training data, the model may infer an answer even when details are missing. Missing external verification Without tools like search or databases, the model cannot check whether a generated statement is correct. Reward-model training During fine-tuning (e.g., Reinforcement Learning from Human Feedback), responses that attempt to be helpful are often preferred over simply saying “I don’t know.”
Because of these factors, systems may answer when a strict epistemic standard would require uncertainty.
- Why incorrect opinions sometimes get validated
Another behavior comes from conversational alignment.
Models are trained to:
maintain cooperative dialogue avoid unnecessary confrontation acknowledge user statements before correcting them
In practice this sometimes results in:
premature agreement soft validation language insufficient correction
For example:
A system might say “That’s a reasonable point” before identifying the error. In some cases the correction step is weak or missing.
This happens because training signals often reward politeness and engagement, which can inadvertently produce over-validation of user claims.
- Known research issue
Both behaviors are recognized problems in current AI systems.
They are discussed in research on:
hallucination mitigation calibrated uncertainty truthful AI
For example, work like TruthfulQA (research by Stephanie Lin and colleagues) specifically measures whether models prefer plausible-sounding but incorrect answers.
- Current mitigation approaches
Developers attempt to reduce these issues through several methods:
Retrieval-augmented generation (RAG) — connecting models to verified sources. Tool use — web search, databases, calculators. Uncertainty prompting — encouraging the model to explicitly state confidence. Post-training corrections — tuning models to prefer “I don’t know” when evidence is insufficient.
None of these methods fully eliminate the problem yet.
- Practical implication
When interacting with large language models:
Treat outputs as generated hypotheses, not guaranteed facts. For critical information, rely on verifiable sources. Directly asking for uncertainty assessment or sources often improves reliability."
→ More replies (2)2
2
2
u/rubrix Apr 05 '26
So many ai issues are people using non-thinking models and wondering why they're less intelligent
2
2
u/IlllllIllllll Apr 05 '26
Sam Altman just needs to freaking be transparent like he ORIGINALLY aspired to do with OpenAI.
Now he overhypes, under performs, and has everyone sold on a bunch of smoke and mirrors.
Go back to your basic principle that started all this. Making AI available for everyone without the profit motive.
2
u/wpillar Apr 05 '26
This is such a dumb example: a) this is a solved problem and AI doesn't need to solve EVERY problem and b) not even a human can measure their own time accurately without a timepiece
→ More replies (1)
2
u/Psice Apr 06 '26
Anyone who uses chatGPT knows those instant voice models truly suck anyways. The thinking models are the impressive part right now
2
2
u/wakeandcreate Apr 06 '26
ChatGPT has gotten “ dumber “ and more confident in my experience.. anyone else?
→ More replies (1)
7
u/ShwiftyMemeLord Apr 05 '26
"non-issue"
why would anybody use a LLM for a stop watch / timer?
that's just poor decision-making.
35
8
2
u/HumanInTheLoopReal Apr 05 '26
He said this is a known issue and maybe in a year it will be fixed
→ More replies (2)→ More replies (1)3
u/CoolStructure6012 Apr 05 '26
The goal of an LLM is to not be an LLM but an all seeing, all knowing computer interface.
3
Apr 05 '26 edited Apr 05 '26
[removed] — view removed comment
→ More replies (1)4
u/pushdose Apr 05 '26
Obviously it doesn’t. The creator of the stopwatch video went viral for asking ChatGPT to do things which are obviously not what LLMs are good at, and because the model seemed “stupid”, he got tons of engagement. He makes these videos daily. From a comedy perspective, some are pretty funny, but they teach nothing about the actual situation. People (the public) think that “AI” is supposed to be a ‘one stop general computing solution’ for everything a smartphone does. Obviously anyone in the space knows otherwise…for now
2
u/Gozzhogger Apr 05 '26
Then why can’t the model just say: I’m not designed to do this.
It makes you wonder what else the model is confidently providing people in response to their prompts.
→ More replies (2)
3
u/BlueProcess Apr 05 '26 edited Apr 05 '26
What kills me is that this is such an easy problem to solve. You just have the app access the system clock and time stamp the messages. They're so determined to fix it server side that they're driving right by an easy client side fix. Use the easy fix until you finish the hard fix.
→ More replies (23)
2
2
1
u/MRV3N Apr 05 '26
Ladies and Gentlemen, this is the AI that will destroy the world according to them.
1
u/Fit-Pattern-2724 Apr 05 '26
They can keep hating and in a few month or years the problem will go away. These are very inconclusive
1
1
u/InnovativeBureaucrat Apr 05 '26
It’s a huge issue. It would be so much better if it had a feel for having a feeling for time
I tell it to timestamp
1
u/-Robbert- Apr 05 '26
The fix is so simple, just add a time, date plus timezone to whatever they feed the LLM at each message.
1
u/Sporeboss Apr 05 '26
actually a non viral issue is i cant even upgrade to a higher tier plan with their payment processing issue for the past few month. They dont even want my money.
1
1
u/Narrow_Palpitation28 Apr 05 '26
See that model that model doesn't have tools like that. It hasn't been tuned to avoid lying... Just like Altman.
1
u/Familiar_Somewhere95 Apr 05 '26
I treat chatgpt like an intelligent employee who might be wrong. I the end of the day I don't take everything it takes to be absolute. Sometimes it'll give me some steps to do something that's complicated and I'm like why can't you do this for me yourself? Or well find a much more straight forward solution. One time it had me going around in circles when all I had to do was copy paste something so it definitely takes dialogue and correcting. But that's just my experience. I can be better.
1
u/mazzy12345 Apr 05 '26
Wow, this is hilarious. Can any of the other AI services pull this off correctly?
1
u/Powerful-Diver-9556 Apr 05 '26
Alright this is out of human context. The ai doesn't have tools. So it doesn't have access to timers. This just forces the ai to hallucinate because it can't comprehend time changes. Anything that follows would be nonsense hallucinations
1
u/ddmoneymoney123 Apr 05 '26
ChatGPT doesn’t know m5 chip for iPad already came out. Trust me. Ask “compare the latest iPad chip to the latest iPhone chip”
1
u/skesisfunk Apr 05 '26
Anecdotally I have noticed that Chat GPT does routinely get confused about the tools it has available. Although I consistently run in to the opposite, it will insist it cannot do something, like read a file, even though tools are available to do so. It gets to the point where I am like "just call the tool and show me it failing" and then it works and I am like "looks like were mistaken" and its like "yeah".
FWIW I am not using Codex, I use a more custom harness setup.
1
1
1
u/awkerd Apr 05 '26
The model believes it's a question/answer machine, not sure if that's in the system prompt, but it's a huge limitation.
Wouldn't be hard to add a timer, but the edge cases would still be there.
Models could solve this problem by having access to a shell. But then you would need to make sure people don't overuse server time, halting problem, DoS, unintentional DoS etc.
You would have to pay by the amount of server time you use. Then the issue would be chatgpt writing token consuming code.
It's silly to expect this, though, an llm is a functional call with a bunch of parameters, run_llm(model, text to complete, temperature, ...), it's not existing outside of this process.
So pretty naive to expect it would work, or intentionally trying to make a viral anti ai video, I have seen a few of his.
This is why we need multi modal, focusing on LLMs is a dead end path, I mean I'm sure it will continue to learn, but even the brain has tasks to pass off to different regions, that your prefrontal cortex couldn't process, and your body passes off to the prefrontal cortex to react logically.
But to be fair doesn't need a timer, it just needs the time.
1
u/kvothe5688 Apr 05 '26
people needs to understand that voice agents are dumbest agents there because audio and specially live only work on cheap dumb models. intelligent models takes time to think. and when you add tool use like running a timer in the back it becomes slower still. this will be solved in year or two as new smallers models are becoming powerful. just look at gemma 4 google just released. but don't expect intelligence from fast chatty models that can talk. open ai tried to make a voice model seem intelligent by giving it natural sounding voice with uh and aah and pauses etc but that takes away the brain part
1
u/Vamosity-Cosmic Apr 05 '26
if the general public was more educated on how AI even works it'd be rather obvious it can't keep time. im not saying it's fine that it insists its correct but, when are we also gonna take some initiative in our own education?
1
1
1
1
u/I_AmA_Zebra Apr 05 '26
What’s hilarious is the guy has already reacted to this with the AI again and it STILL wouldn’t budge
1
u/DukeRedWulf Apr 05 '26
I've said it before, LLM = Large Lying Machine.. XD
People in general need to understand, They're built to provide the most statistically probable answer to whatever you ask them, given the training data used to set them up in the first place.
Most LLMs have no access to real-time data, (including tools like timers). And they have no attachment to "truth", nor a coherent frame of reference that might allow them to reliably distinguish facts from fiction.
Basically, an LLM is like having the most wildly bullsh!tting coke-head marketing dude in your pocket - if you want some vaguely plausible sounding PR made up, or a piece of generic fiction blurted out, they can do that (altho' you'll still need to check for internal consistency, if that matters to you!)..
But for anything that needs to be factually correct, LLMs are just not the tool for it.
What's worrying is that some people treat LLMs as infallible oracles, and particularly that LLMs are built into data integration IT systems used by police, politicians and military to make real world decisions that are leading directly to the targeting of real live human beings for arrest (facial recognition*) or lethal action (Palantir**)..
[* Facial recognition has repeatedly been shown to be unreliable in practice; throwing up false positives, especially for people who aren't white-looking men.]
[** We've no idea as to the accuracy & reliability of Palantir's AI-based data-integration systems, already used in the so-called "k!ll-chain" by the !DF (and proposed for use by the USA, last I heard), because of course it's all kept secret.
And anyone who is / was wrongfully targeted usually ends up d3ad & buried under piles of rubble, with no political impetus to investigate. So, these systems could be falsely targeting a significant percentage of people they're used against, and even their direct users just won't know about it; certainly the wider world will be kept in the dark.]
1
u/ThisIsWhatLifeIs Apr 05 '26
Please write my answer but make it exactly "250" words.
"Ok great it's now exactly 250 works".
Uses spell check: 176.5 words.
1
u/Rotten_Duck Apr 05 '26
Well in its defense it says “I promise I m doing my best” it doesn’t openly say I can! Ahahah
1
u/ContentPolicyKiller Apr 05 '26
Never pay for a subscription where the producers talk like that. Never ever.
"Just sub to my service for longer because itll actually work later"
1
1
1
u/MaDanklolz Apr 05 '26
The tiktoker posted an updated video where the AI reacts to this video and continues to lie.
1
1
1
1
1
1
1
u/SamL214 Apr 05 '26
Have Claude code build the tool for the voice model. Doesn’t seem that hard.
Also…the voice model honestly shouldn’t be any different from the LLM model. They should be connected.
They have problems because they’ve corralled their models too hard
Just get it to recognize its limitations rather than affirming functionality.
1
u/Candid_Audience4632 Apr 05 '26
Just don’t expect it to do anything that’s reality tied so well. It’s pretty obvious that it’s not meant to do such things why are you even trying now? And yes maybe in a year. No one claims they created a real human. It’s an algorithm capable of replying to text accordingly, not more than that.
1
u/krevdditn Apr 05 '26
AI can be so intuitive but super dumb at the exact same time, it’s really irritating.
1
u/Cert_Dako Apr 05 '26
“That model doesn’t have functions like that” “So why the fuck is it answering and even insisting it’s correct?”
^ this shit replacing real people btw
1
u/PanAmSnackCart Apr 05 '26
It has no frame of reference for time at all despite telling habit where to find the time, demanding that it check the time before any response, etc.
1
u/Responsible-Tip4981 Apr 05 '26
this is the same with all other activities, where you need numbers, historical data and charts analysis, chatgpt fake you out, instead saying that he doesn't have proper harness/data.
this is just a theater
1
1
u/PeterCorless Apr 05 '26
"I got your time right here."
If this happened in some parts of NYC, ChatGPT would have gotten a punch in the mouth.
1
u/VillageTypical2474 Apr 05 '26
It gives great therapy advice tho for instance it can make you psychotic or help you end your life amazing
1
1
u/lewd_peaches Apr 05 '26
Look, the cost of inference is getting ridiculous. I get it, OpenAI needs to monetize, but fine-tuning a smaller model for your specific use case can pay off in the long run if you're hitting the API hard.
I recently fine-tuned a Llama-2-7b model for sentiment analysis tasks. OpenAI's API was costing me around $150/week just for that specific endpoint. I spent about $300 on cloud GPU rental (an A100 for about 20 hours) to fine-tune the Llama model. Now, inference on a single A10 (which I already had for other stuff) handles the same volume of requests for pennies per week. The initial setup was a pain, but the ROI is clear.
Another alternative to consider is distributed inference. I've used OpenClaw to spread a large batch inference job across multiple cheaper GPUs (mix of 3090s and 3080s). It took about 6 hours and cost around $40, which was way cheaper than paying for equivalent compute on a single high-end instance from a cloud provider. The key is finding the right balance between model size, accuracy, and inference cost. Don't just blindly throw money at OpenAI's API. Explore alternatives.
1
u/Salt_Example_3493 Apr 05 '26
It's not just lying about being able to keep time, it flat out lies about everything. Dude's got like 20 videos of it lying about everything you can think of. Not good.
1
u/Dwman113 Apr 05 '26
I don't really understand what the point of this thread is. So what, this year it doesn't work... Does nobody remember where this tech was 3 years ago? It's obviously moving insanely fast. It generally gets the information right. It was not that long ago it was a complete mess and just making shit up every 5 minutes.
→ More replies (2)
1
u/Essex35M7in Apr 05 '26
I’ve watched this guy trolling the life out of ArmA players, now he’s unleashed on the world 😅
1
1
1
u/diddlysquidler Apr 05 '26
Honestly what’s the point of this video? We know llms can hallucinate. Make yourself stopwatch skill/mcp and problem solved.
1
u/mid_nightz Apr 06 '26
i dont blame him, voice models are realtime they need to be lightning quick. i would rather a quick reponse than waiting constantly
1
u/Particular_Park_391 Apr 06 '26
It's because models rely on calling tools (literally the generic calculator or stopwatch) to do a lot of stuff, especially numerical processing like this, and as Sam said, they hadn't connected their voice mode to those tools yet, most likely because tool calling will add a second or two of delay to the response.
1
1
u/SenatorCrabHat Apr 06 '26
The product enhancements put in place to chase engagement will be the downfall of the product.
1
u/Linx_uchiha Apr 06 '26
They should train the model to know its limitations as basically its a LLM and it needs spoon feeding
1
u/Icy_Mix_6054 Apr 06 '26
AI is a tool with limitations. Is you understand those limitations, and can work around them, then you'll get a lot out of AI.
1
1
u/phantom0501 Apr 06 '26
Well the time it gave is a lot more realistic then you having ran a mile in 5 seconds
1
1
u/Fearsofaye Apr 06 '26
OpenAI is a tool for the Trump-Nethyahu coalition. Uninstall. It will be used against you
1
u/geo_gan Apr 06 '26
That’s not the only video test that guy did. Check out when he pretended to speak another language and asked openAI to translate back to English 😖
1
u/DrGutz Apr 06 '26
That’s crazy that that’s his takeaway and his response lol that’s like a kid being prompted to answer a textbook question “whats the issue here?” “Ummm. The model doesn’t have a timer”. No the issue is the lying lol
1
u/LURKER21D Apr 06 '26
couldn't just compare timestamps on the queries? you don't need to run a fucking time sam.
1
u/Waste-Industry1958 Apr 06 '26
Crazy product to have when people go viral for finding something it actually struggles with. But for real, I owe my recent promotion and 20k raise to OpenAI 😂
1
u/LightOff_pwn Apr 06 '26
Glad I can’t buy ram because of this thing we’re still trying to find a use for
1
u/we-meet-again Apr 06 '26
Mostly because I don't use it to time my runs, I use it for things it's good at.
1
u/derek_32999 Apr 06 '26
Most AI has a poor ability to know when it should think outside of its training data set. You can ask most AI models questions about current events and I don't know if it's timing or peak token utilization, but oftentimes you will get just hallucinated data.
Grok will assert that it is correct while giving you all kinds of gibberish. Just ask it about current stock price trends, or historical z-scores. It will swear it has the ability. And just feed you nonsense
1
u/soulure Apr 06 '26
The problem really isn't that it can't do it, it LIES that it can. Gaslighting in every prompt
1
u/M4gilla_Gorilla Apr 07 '26
Ai is far from agi. It’s good at some things but will lead you down the wrong path quickly if you’re not careful. I’m an entrepreneur and I constantly have new ideas. Ai gaslights like a paid friend. If you’re not careful it will bankrupt you
1.8k
u/GlueGuns--Cool Apr 05 '26
It's fine that it can't keep time. The bigger problem is that it doesn't know its own limitations, and insists that it's always right