> Do you know why it's so expensive? I'd thought serving html would be cheaper, particularly at Facebook's scale.
I don't know about Facebook specifically, but in general people underestimate the amount of stuff that needs to happen for a consumer-facing app of that scale. It's not just "serving html".
There are going to be thousands of teams with job functions to run thousands of services or workflows doing something incredibly obscure but that's necessary for some regulatory, commercial or operational reason. (Yes, moderation would be one of those functions).
> Also, even still, $10 per user has got to be an order of magnitude less than what OpenAI is spending on its free users, no?
No. OpenAI's inference costs in 2024 were a few billion (IIRC there are two conflicting reports about the leaked financials, one setting the inference costs at $2B/year, the other at $4B/year). That's the inference costs for both their paid subscription users, API users, and free consumer users. And at the time they were reported to have 500M monthly active users.
Even if we make the most extreme possible assumptions for all the degrees of freedom (all costs can be assigned to the free users rather than the paid ones, the higher number for total inference spend, monthly users == annual users), the cost per free user would still be at most $8/year.
I don't know about Facebook specifically, but in general people underestimate the amount of stuff that needs to happen for a consumer-facing app of that scale. It's not just "serving html".
There are going to be thousands of teams with job functions to run thousands of services or workflows doing something incredibly obscure but that's necessary for some regulatory, commercial or operational reason. (Yes, moderation would be one of those functions).
> Also, even still, $10 per user has got to be an order of magnitude less than what OpenAI is spending on its free users, no?
No. OpenAI's inference costs in 2024 were a few billion (IIRC there are two conflicting reports about the leaked financials, one setting the inference costs at $2B/year, the other at $4B/year). That's the inference costs for both their paid subscription users, API users, and free consumer users. And at the time they were reported to have 500M monthly active users.
Even if we make the most extreme possible assumptions for all the degrees of freedom (all costs can be assigned to the free users rather than the paid ones, the higher number for total inference spend, monthly users == annual users), the cost per free user would still be at most $8/year.