AI's economics don't make sense
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AI's economics don't make sense
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Re: AI's economics don't make sense
#2It's interesting to compare it to electricity. Basically Anthropic was selling a flat fee electricity subscription, and when someone started connecting expensive washing machines (OpenClaw) to their subscriptions, instead of changing the pricing model, they banned washing machines...
I wonder if we will get to "electricity" style pricing for AI. What makes electricity predictable is relatively constant average usage over time + price is manageable. I'm just not buying electrical house heating and manage my electricity spending within some bounds.
With AI the problem is that we are only now getting to useful AI, and for now it's still too expensive to be useful, so they subsidize until they can stabilize at "cheap enough and smart enough" level. But it feels like that's still 2 years away while they are stopping to subsidize now. Will be interesting.
Re: AI's economics don't make sense
#3Re: AI's economics don't make sense
#4The truth is that the AI companies are gambling that inference cost will continue following a hyper version of Moore's Law, e.g. Google TurboQuant.
The countervailing thesis is that frontier models are consuming more and more compute.
The deepest truth: you often don't need a frontier model to get commercially acceptable results from AI. Thus, bring on the true pricing! and I'll just switch models to something financially sustainable.
Re: AI's economics don't make sense
#5Re: AI's economics don't make sense
#6Yeah. And weird pricing seems like it's winding down. It's interesting to compare it to electricity. Basically Anthropic was selling a flat fee electricity subscription, and when someone started connecting expensive washing machines (OpenClaw) to their subscriptions, instead of changing the pricing model, they banned washing machines... I wonder if we will get to "electricity" style pricing for AI. What makes electri…
Re: AI's economics don't make sense
#7I pray this happens soon, but I feel I've been hearing some version of it for a while.
Re: AI's economics don't make sense
#8>At some point, the incredible, toxic burn-rate of generative AI is going to catch up with them, which in turn will lead to price increases, or companies releasing new products and features with wildly onerous rates (..) that will make even stalwart enterprise customers with budget to burn unable to justify the expense. I pray this happens soon, but I feel I've been hearing some version of it for a while.
Re: AI's economics don't make sense
#9>At some point, the incredible, toxic burn-rate of generative AI is going to catch up with them, which in turn will lead to price increases, or companies releasing new products and features with wildly onerous rates (..) that will make even stalwart enterprise customers with budget to burn unable to justify the expense. I pray this happens soon, but I feel I've been hearing some version of it for a while.
This tech has uses. It has quite a lot of them in fact. However there is no usage of ChatGPT or Claude that makes OpenAI or Anthropic worth anything fucking close to what they're valued at right now, and both firms are scrambling to figure out how to get down from the top of the AI house of cards without detonating in the process.
Meanwhile DeepSeek is coming out with more capable models that run on far less onerous hardware and with far less compute requirements that does basically exactly what the vast majority of users actually want it to do.
This is going to be a financial bloodbath. Not for anyone actually responsible for it, of course, they'll be fine. It'll be everyone else getting soaked which is the only reason I give two shits.
Re: AI's economics don't make sense
#10How many tokens can you realistically burn through in one chat session? Opus and many other frontier models do maybe 60tok/s, less 250k/hr out. In you can use more, but in most cases cache is 5-10:1 cheaper than new input. Say you average 500ktok in, 90% cache, per request. That amounts to 100-150ktok in new input-equivalent costs, which in most cases is ~20-30ktok in output-equivalent costs. Do a request every minute, that's a total of about 1.5-2Mtok/hr. At API prices that's $50/hr for Opus, but really it probably only costs Anthropic $10/hr to serve that.
That said, even if a developer is burning $50/hr, many, many employees at large companies cost more than $100k/yr to employ all costs considered, so making them say 20-30% more productive can easily make that worth it for most. If the labs shave their margins ultimately to more like 20-30%, you'd have ~$15/hr in costs to use the services, and nearly every white collar job is way over 30k/yr to employ. If your salary is 80k, you probably cost the company 200k all in, so making you 15% more productive offsets the $15/hr cost.
So first party providers are not in a horrifying position or anything from a subsidization standpoint. The people in bad shape are Cursor and Perplexity, who don't have frontier models and are dependent on the open source community, which is typicly 6-12 months behind the frontier. They have to pay full freight API costs at 80% margin for the big boys to serve their harnesses, which is indeed untenable, and they'll have to either force users to use open source models and/or in house models they can serve at-cost or they will have to charge vastly more.
Gemini, Claude, and ChatGPT first-party services like Antigravity, Codex, and Claude Code are not in serious trouble though.