41–50 of 60 posts
How do we make subscribers become equally comfortable paying for AI usage? Tokens, credits, inference calls?
Earlier quoted context omitted.
> Consumers would just use the underlying foundational models directly to solve their problem. ChatGPT and Claude and Gemini are the products, not your business. How am I going to use ChatGPT instead of, say, Figma or an office suite with my coworkers?? It's no use for it to spin up a clone for me if my coworkers can't collaborate. And if they can, what it will serve is a product. How can it be cheaper for every comp…
> How can it be cheaper for every company to re-invent the wheel? Companies not matching their prices to current reality, mostly.
common misconception about software unit economics. With enterprise software (one that costs real $$$) there always more costs attached post shipping. Before client/server it was support. Then it was security and the constant threat of cyber attacks.
Distributing software is nothing like distributing books.
"Inference" is just software running. It has always cost money to run software, it's just that it is generally too cheap to matter. If a client makes a regular API call to your server, you pay for that compute, probably in the form of a flat hosting fee. If too many calls come in and workload goes up, you pay for a more expensive hosting tier to handle it (or do dynamic scaling which is per-unit of compute). Right no…
The article have talked about this:
> You cannot, however, build a business model today on a cost breakthrough that has not happened yet. Even if costs do fall, Jevons paradox[5] tends to kick in: historically, when a resource gets cheaper, we find more uses for it rather than consuming less. Cheaper inference does not get banked as margin improvement; it gets consumed by deeper integration, more calls per interaction, more autonomous agents running in the background. The cost per call drops but the calls per user multiply.
I think part of the new equation may also become; "Why even pay for the SaaS in the first place if you can just forge the service exactly how you want it?" The benefits of unlimited access to the tool you forge are still there, its just a lot easier to make whatever tool you want. Are there any examples of products containing ai inference that are successful? Products that are beyond just direct access to frontier LL…
Most LLM-using mobile games are already at incredibly weak TTP scores and perhaps the only current stratum of mobile games where TTP is almost always ahead of TTFA. TTFA before TTP is almost nonexistent because they claim to need a monthly subscription as soon as immediately after install, despite being advertised as free to start. It's also one of the few types of games where the paywall explicitly does not include "no ads". Some of these games running on monthly subscriptions still need ads for unit costs.
(The bulk of mobile games try for a sweet spot of TTFA in the order of hours of gameplay and TTP in the order of days of gameplay. Easier to get people hooked on your game if you can give them a few hours of uninterrupted fun up front.)
It seems pretty condemning of software economics with LLMs involved.
Earlier quoted context omitted.
As if making all the decisions that go into that product, hosting it, and maintaining it are free! Now do that for all the SaaS you subscribe to. Would you even get any real work done?
There wouldn't be a product. Consumers would just use the underlying foundational models directly to solve their problem. ChatGPT and Claude and Gemini are the products, not your business. Products are only viable when you do a lot of work to solve a problem, which is then shared by many potential customers. It makes sense to amortize the high costs of solving the problem across all the different customers to reap ec…
Whether this could happen is a critical question.
What ive found currently is that its not possible because the non-determinism of the model means you cant trust it, and these tasks are such that people expect determinism. Even if they dont then they dont tolerate the kind of stupid mistakes these models make
What could happen is that the model becomes good enough to be near deterministic, or as deterministic as humans. I dont know if the current next token prediction foundation is sufficient for that. But who knows, maybe it is
I think part of the new equation may also become; "Why even pay for the SaaS in the first place if you can just forge the service exactly how you want it?" The benefits of unlimited access to the tool you forge are still there, its just a lot easier to make whatever tool you want. Are there any examples of products containing ai inference that are successful? Products that are beyond just direct access to frontier LL…
As if making all the decisions that go into that product, hosting it, and maintaining it are free! Now do that for all the SaaS you subscribe to. Would you even get any real work done?
About design and the product side of maintainance, what i have felt is that, deep down inside, the user does know exactly what they need. If they can learn to communicate that in a way another person or agent can understand, then design and maintainance will be fine. Thats a big if, but if the economics align for people to benefit from developing that skill, maybe they do.
I think part of the new equation may also become; "Why even pay for the SaaS in the first place if you can just forge the service exactly how you want it?" The benefits of unlimited access to the tool you forge are still there, its just a lot easier to make whatever tool you want. Are there any examples of products containing ai inference that are successful? Products that are beyond just direct access to frontier LL…
This is the part I'm least convinced by.
Corporates used to develop their own tools and they moved away from it for many reasons. Cost of development was only one of those reasons.
Earlier quoted context omitted.
> If you buy your own GPU, rack it, and run an open model, there is no unit cost. No. There is economic opportunity cost (borrowing), energy cost, infra cost, depreciation / risk of failure with each unit of work, bandwidth, maintenance, and lots more. Small, but not zero, and often overlooked - especially the opportunity cost.
> opportunity cost We need a better word for this because the things you didn't do are not a cost