This is part of the reason why I'm really worried that this is all going to result in a greater economic collapse than I think people are realizing.
I think companies that are shelling out the money for these enterprise accounts could honestly just buy some H100 GPUs and host the models themselves on premises. Github CoPilot enterprise charges $40 per user per month (this can vary depending on your plan of course), but at this price for 1000 users that comes out to $480,000 a year. Maybe I'm missing something, but that's roughly what you're going to be spending to get a full fledged hosting setup for LLMs.
Most companies don't want to host it themselves. They want someone to do it for them, and they are happy to pay for it. If it makes their lives easier and does not add complexity, then it has a lot of value.
Out of curiosity, how many concurrent users could you get with a hosting setup at that price? If let's say 10% of those 1000 users were using it at the same time would it handle it? What about 30% or 100%?
You made a good point that I didn't think through fully. It's the concurrent user aspect that heavily impacts things. Currently, you'd probably need quite a bit more investment to the point of having a mini data center to do what I'm proposing.
However, we've been seeing advancements in compressing context and capabilities of smaller models that I don't think it'd be too far off to see something like what I'm talking about within the next 5 years.
Honestly, I think part of the reason Apple hasn't jumped deep into AI is due to two big reasons:
1) Apple is not a data company.
2) Apple hasn't found a compelling, intuitive, and most of all, consistent, user experience for AI yet.
Regarding point 2: I haven't seen anyone share a hands down improved UX for a user driven product outside of something that is a variation of a chat bot. Even the main AI players can't advertise anything more than, "have AI plan your vacation".
Put proper LLM into Siri. Encourage developers to expose the functionality of their apps as functions, allow Siri LLM to access those (and sprinkle some magic security dust over it).
Boom, you have an agent in the phone capable of doing all the stuff you can do with the apps. Which means pretty much everything in our life.
I'm pretty sure most people didn't notice any kind of inconsistency. I myself have a hard time figuring out what's going on. I'm so focused on doing the work with the computer that I don't have the time to notice what's "wrong" with the OS. Which makes me wonder if the whole thing is blown out of proportion.
No, I don't think so. You've paid for a service that will run an AI model given some prompt. There have been zero guarantees made that it will actually solve your problem.
As others have stated too, how do you define what an incorrect output is?
Chegg is a service many students used to get guidance and answers to homework problems for whatever courses they were taking. It was a sinking ship once GPT 4 came out, but GPT 5 was really it's final nail in the coffin.
> I am suspicious of grifters and would like to find trustworthy advice.
If you want actual good advice: go to a doctor.
Don't go to a chiropractor, don't go to hackernews. Go to a doctor. You can either start with a physical therapist in your area or start with your primary care doctor to get a referral.
I'm assuming you're in the US, so I know it's expensive but this will genuinely shorten your life span if you let it get significantly worse.
I think companies that are shelling out the money for these enterprise accounts could honestly just buy some H100 GPUs and host the models themselves on premises. Github CoPilot enterprise charges $40 per user per month (this can vary depending on your plan of course), but at this price for 1000 users that comes out to $480,000 a year. Maybe I'm missing something, but that's roughly what you're going to be spending to get a full fledged hosting setup for LLMs.
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