OpenAI Is A Bad Business
OpenAI Is A Bad Business
www.wheresyoured.at
OpenAI Is A Bad Business
41 comments
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I pooh-poohed ChatGPT when it first came out so I gave it another crack at a technical issue I’ve been avoiding.
Gave me an outdated answer.
Gave me another outdated answer to a URL that doesn’t exist.
Gave me the answer I told it won’t work in the initial prompt.
Scolded me for swearing at it.
This is what’s supposed to replace search engines?
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Then as you ask "provide sources.", it says simply "Source: Tech Review Websites". If this came from an actual person I would genuinely ask it "do you take me for gullible trash?".
It's still somewhat useful, due to Google Search crumbling away into nothingness, if you ask "link me five sites with info about [topic]".
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Your experience highlights what current iterations of LLMs are not well suited for, so I understand if that's what you were hoping to achieve, why you were left wanting, or disillusioned.
There's a lot of things that LLMs are really good at, or incredibly useful for, such as ingesting large bodies of text, and then analyzing them based on your ability to create well thought out prompts.
This can save you hours and hours, of reading time, and it's something that you can verify the answer on relatively quickly, to double check the LLMs response accuracy.
They're also good at doing something Google used to be good at, but sucks at now. Which enabling you to describe process, simple or complicated, short or long, that you either can't recall the name of, or aren't even sure where it's called, and letting you know exactly what it is. Also, easily verifiable.
There's plenty of other things too, but just remember that they are tools, not magic, or sentient intelligence.
The models are not real time, but there are tricks to figure out it's most recent dates of ingestion, such as asking topical entertainment or news questions, but don't go looking for a real-time information.
Also, I have yet to find a model that can provide an actual URL and specific source for anything it generates, which is why it's a good practice to use them to do tasks, or get information, that would take you longer to do, or get, manually, but that can be easily verified once you receive it.
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There's a lot of things that LLMs are really good at, or incredibly useful for, such as ingesting large bodies of text, and then analyzing them based on your ability to create well thought out prompts.
That's the story people tell at least. The weasel phrase at the end is fun, I guess. Leaves a massive backdoor excuse when it doesn't actually work.
But in practice, LLMs are falling down even at this job. They seem to have some yse in academic qualitaruve coding, but for summarizing novel or extended bodies of text, they struggle to actually tell people what they want to know.
Most people do not give a shit if text contains a reference to X. And if they do, they can generally just CTRL+F "X".
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Scolded me for swearing at it.
"You'll fucking know when I'm swearing at you," was my reply to that shit the last time I gave it a spin (after it regurgitated nonsense after many prompts specifically asking for not nonsense).
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I hope sonething better comes along because google ruined their search engine a decade ago. stract.com is probabky the closest to what google used to be.
As for chatgpt, it is not an index. It cannot refer you back to infornation it was trained on because it doesn't build a massive indexed internet database.
It has some method of probable relations and conglomerarion of input. It is why it "hallucinates" information output, because it doesn't "know" what is wrong or right info, it just fetches data based on probabilities of connections.
It is good at suggesting new music or movies based on your list of media you like, but it is terrible with actual factual info
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O no, you mean the AI hype is another bs tech bubble?!
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The funniest part is that all the AI hype is focused on all the wrong things. There are absolutely great AI tools that get very little mention.
For example, I'm visually impaired and use AI tools A fair bit to help me get around the internet and such. Especially when it comes to using AI I to generate descriptions of images.
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O that's very cool! I also heard it's super good for auto subtitles (which admittedly is a bad thing for people doing that for a living 😿).
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A 100+ billion dollar valuation.
Absurd.
It's just as absurd as when WeWork got a 40 billion dollar valuation.
These VC's are insane and should be paying a high-as-fuck tax rate instead of having a bazillion dollars to drop on boondoggles.
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Ed is getting good at lobbing these darts at hype bubbles.
The thing that this writeup ignores is that the object isn't to show short-term revenue, but to put all competitors out of business, be the last one standing, and create a monopoly. Either that or get bought out so the investors can move on to the next thing. But at $150B valuation, only MSFT or Nvidia can afford to buy them outright.
Google, Meta, and Amazon burned through cash for years, but they eventually outran all competition and then monetized the users who had nowhere else to go.
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See that it's never going to make money, go public, hand the keys over to someone else, and then try again with a wallet full of cash and a reputation for making billion dollar businesses.
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Meanwhile people say way too personal stuff to chatgpt, copilot, bing, jetbrains, apple intelligence, etc.
I'm suspecting this might get sold off to data brokers
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One thing I'd push back on in the article is:
That cost-per-user doesn’t decrease as you add more customers. You need more servers. More GPUs.
This is assuming constant use, which is not the case. If I have a server handling LLM prompt requests, and for illustrative purposes each request uses 100% of the single discrete GPU in it, and I only have 1 customer, but that one customer only uses it 5% of the day (which would actually be pretty high in real terms), I can still add additional customers without needing to buy additional servers. The question is whether the given revenue of a single server outweighs its cost to run.
And when it comes to training, that is an upfront cost, that you could (if you get a model to where you want it) stop having to pay whenever you want. I'm pretty surprised they haven't been really leaning into training models for medical diagnoses, because once you have a model that can e.g. spot a type of tumor with n% accuracy beyond a human, you don't really have to refine it further if you don't want to (after all, it's not like the humans can choose to do it better themselves at that point, like they can with writing prompts).
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I'd say they've probably long reached the point where they have enough customers around the world to hold the load on their servers fairly constant. The example with one user only taking 5% of a servers load only works for low customer counts, similar to how you can't count on one wind turbine or solar plant to provide all of your energy but if you have enough of them you can provide a base line of fairly constant energy
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And a few people will get extremely rich by siphoning off a percent or two, circle of life baby /s
41 comments