←back to thread

Microsoft and OpenAI's close partnership shows signs of fraying

(www.nytimes.com)
321 points jhunter1016 | 2 comments | 18 Oct 24 11:11 UTC | HN request time: 0.001s | source
Show context
Roark66 ◴[18 Oct 24 12:02 UTC] No.41878594[source]▶
>OpenAI plans to loose $5 billion this year

Let that sink in for anyone that has incorporated Chatgpt in their work routines to the point their normal skills start to atrophy. Imagine in 2 years time OpenAI goes bust and MS gets all the IP. Now you can't really do your work without ChatGPT, but it cost has been brought up to how much it really costs to run. Maybe $2k per month per person? And you get about 1h of use per day for the money too...

I've been saying for ages, being a luditite and abstaining from using AI is not the answer (no one is tiling the fields with oxen anymore either). But it is crucial to at the very least retain 50% of capability hosted models like Chatgpt offer locally.

replies(20): >>41878631 #>>41878635 #>>41878683 #>>41878699 #>>41878717 #>>41878719 #>>41878725 #>>41878727 #>>41878813 #>>41878824 #>>41878984 #>>41880860 #>>41880934 #>>41881556 #>>41881938 #>>41882059 #>>41883046 #>>41883088 #>>41883171 #>>41885425 #
hmottestad ◴[18 Oct 24 12:16 UTC] No.41878683[source]▶
Cost tends to go down with time as compute becomes cheaper. And as long as there is competition in the AI space it's likely that other companies would step in and fill the void created by OpenAI going belly up.
replies(2): >>41878721 #>>41878929 #
ToucanLoucan ◴[18 Oct 24 12:47 UTC] No.41878929[source]▶
> Cost tends to go down with time as compute becomes cheaper.

This is generally true but seems to be, if anything, inverted for AI. These models cost billions to train in compute, and OpenAI thus far has needed to put out a brand new one roughly annually in order to stay relevant. This would be akin to Apple putting out a new iPhone that costed billions to engineer year over year, but was giving the things away for free on the corner and only asking for money for the versions with more storage and what have you.

The vast majority of AI adjacent companies too are just repackaging OpenAI's LLMs, the exceptions being ones like Meta, which certainly has a more solid basis what with being tied to an incredibly profitable product in Facebook, but also... it's Meta and I'm sure as shit not using their AI for anything, because it's Meta.

I did some back of napkin math in a comment a ways back and landed on that in order to break even merely on training costs, not including the rest of the expenditure of the company, they would need to charge all of their current subscribers $150 per month, up from... I think the most expensive right now is about $20? So nearly an 8 fold price increase, with no attrition, to again break even. And I'm guessing all these investors they've had are not interested in a 0 sum.

replies(2): >>41881018 #>>41881375 #
1. authorfly ◴[18 Oct 24 17:08 UTC] No.41881375[source]▶
This reasoning about the subscription price etc is undermined by the actual prices OpenAI are charging -

The price of a model capable of 4o mini level performance used to be 100x higher.

Yes, literally 100x. The original "davinci model" (and I paid $5 figures for using it throughout 2021-2022) cost $0.06/1k tokens.

So it's not inverting in running costs (which are the thing that will kill a company). Struggling with training costs (which is where you correctly identify OpenAI is spending) will stop growth perhaps, but won't kill you if you have to pull the plug.

I suspect subscription prices are based on market capture and perceived customer value, plus plans for training, not running costs.

replies(1): >>41887216 #
2. ToucanLoucan ◴[19 Oct 24 11:30 UTC] No.41887216[source]▶
> So it's not inverting in running costs (which are the thing that will kill a company). Struggling with training costs (which is where you correctly identify OpenAI is spending) will stop growth perhaps, but won't kill you if you have to pull the plug.

I don’t think it’s that cut and dried though. Many users run into similar issues as other issues with things like reasoning (which is (allegedly) being addressed) and hallucinations (less so) both of which in turn become core reasons for subsequent better versions of the tech. Whether the subsequent versions deliver on those promises is irrelevant (though they often don’t) to that, at least IMHO, being a core reason to “stay on board” with the product. I have to think if they announced tomorrow they couldn’t afford to train the next one that there would be a pretty substantial attrition of paying users, which then makes it even harder to resume training in the future, no?