121–130 of 409 posts
I should? what problems can I solve, that can be only done with an agent? As long as every AI provider is operating at a loss starting a sustainably monetizable project doesn't feel that realistic.
I love how programmers generally tout themselves as these tinkerers who love learning about and exploring technology… until it comes to AI and then it’s like “show me the profitable use case.” Just say you don’t like AI!
I should? what problems can I solve, that can be only done with an agent? As long as every AI provider is operating at a loss starting a sustainably monetizable project doesn't feel that realistic.
The post is just about playing around with the tech for fun. Why does monetization come into it? It feels like saying you don't want to use Python because Astral, the company that makes uv, is operating at a loss. What?
If the Apis I call are not profitable for the provider then they won't be for me either.
This post is a fly.io advertisement
Earlier quoted context omitted.
> As long as every AI provider is operating at a loss None of them are doing that. They need funding because the next model has always been much more expensive to train than the profits of the previous model. And many do offer a lot of free usage which is of course operated at a loss. But I don't think any are operating inference at a loss, I think their margins are actually rather large.
> But I don't think any are operating inference at a loss, I think their margins are actually rather large. Citation needed. I haven't seen any of them claim to have even positive gross margins to shareholders/investors, which surely they would do if they did.
Earlier quoted context omitted.
Parent comment never said operating inference at a loss, though it wouldn't surprise me, they just said "operating at a loss" which they most definitely are [0]. However, knowing a few people on teams at inference-only providers, I can promise you some of them absolutely are operating inference at a loss. 0. https://www.theregister.com/2025/10/29/microsoft_earnings_q1...
> Parent comment never said operating inference at a loss Context. Whether inference is profitable at current prices is what informs how risky it is to build a product that depends on buying inference, which is what the post was about.
The first obvious limitation of this would be that all models would be frozen in time. These companies are operating at an insane loss and a major part of that loss is required to continue existing. It's not realistic to imagine that there is an "inference" only future for these large AI companies.
And again, there are many inference only startups right now, and I know plenty of them are burning cash providing inference. I've done a lot of work fairly close to the inference layer and getting model serving happening with the requirements for regular business use is fairly tricky business and not as cheap as you seem to think.
Earlier quoted context omitted.
So AI companies are profitable when you ignore some of the things they have to spend money on to operate? Snark aside, inference is still being done at a loss. Anthropic, the most profitable AI vendor, is operating at a roughly -140% margin. xAI is the worst at somewhere around -3,600% margin.
If they are not operating inference at a loss and current models remain useful (why would they regress?), they could just stop developing the next model.
I should? what problems can I solve, that can be only done with an agent? As long as every AI provider is operating at a loss starting a sustainably monetizable project doesn't feel that realistic.
I love how programmers generally tout themselves as these tinkerers who love learning about and exploring technology… until it comes to AI and then it’s like “show me the profitable use case.” Just say you don’t like AI!
I should? what problems can I solve, that can be only done with an agent? As long as every AI provider is operating at a loss starting a sustainably monetizable project doesn't feel that realistic.
The post is just about playing around with the tech for fun. Why does monetization come into it? It feels like saying you don't want to use Python because Astral, the company that makes uv, is operating at a loss. What?
I should? what problems can I solve, that can be only done with an agent? As long as every AI provider is operating at a loss starting a sustainably monetizable project doesn't feel that realistic.
I love how programmers generally tout themselves as these tinkerers who love learning about and exploring technology… until it comes to AI and then it’s like “show me the profitable use case.” Just say you don’t like AI!
Its about balance.
Really its the AI providers that have been promising unreal gains during this hype period, so people are more profit oriented.
Earlier quoted context omitted.
If they are not operating inference at a loss and current models remain useful (why would they regress?), they could just stop developing the next model.
They could, but that’s a recipe for going out of business in the current environment.