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OpenAI has temporarily stopped selling the Plus plan

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Re: OpenAI has temporarily stopped selling the Plus plan

#4
post #2

The comments are so ignorant it's unreal. I think the OpenAI team is doing their best. I've heard it's actually hard to scale an app to 100+ million users

GPT-4 is the greatest software developer in the world. I'm sure that it can scale itself easily.

Re: OpenAI has temporarily stopped selling the Plus plan

#5
post #2

The comments are so ignorant it's unreal. I think the OpenAI team is doing their best. I've heard it's actually hard to scale an app to 100+ million users

GPT-4 is the greatest software developer in the world. I'm sure that it can scale itself easily.

commit hash: deadbeef

commit author: GPT-4

commit message: ":rocket_emoji: Set all Azure clusters to autoscale in order to resolve flooded message queue"

Re: OpenAI has temporarily stopped selling the Plus plan

#6
post #2

The comments are so ignorant it's unreal. I think the OpenAI team is doing their best. I've heard it's actually hard to scale an app to 100+ million users

GPT-4 is the greatest software developer in the world. I'm sure that it can scale itself easily.

[dead]

Re: OpenAI has temporarily stopped selling the Plus plan

#8
GPT3 has 175 billion parameters and Altman said 4 would use way more compute than 3.

Let's just look at GPT 3. Each forward pass requires 2N=350B flops per token. The computational overhead of the attention mechanism is negligible but the memory overhead of the attention for all users is not, but we can ignore that for now. Let's assume each query involves ~200 tokens of combined input and output. That's 70T flops per query. Let's say the cost of compute is 1 cent per 100B flops (probably a lowball). That's $7 per query for compute alone.

And that's just GPT 3.

Re: OpenAI has temporarily stopped selling the Plus plan

#10
post #8

GPT3 has 175 billion parameters and Altman said 4 would use way more compute than 3. Let's just look at GPT 3. Each forward pass requires 2N=350B flops per token. The computational overhead of the attention mechanism is negligible but the memory overhead of the attention for all users is not, but we can ignore that for now. Let's assume each query involves ~200 tokens of combined input and output. That's 70T flops pe…

I mean, that might be the cost for a onesie-twosie in Azure, but if you're microsoft and you own the hardware, the cost may be one or more orders of magnitude less than that. (Of course, there's just a limit on the number of GPUs that exist and that Nvidia can pump out.)
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