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There is something I have been pondering recently. If we compare the cost of AI subscriptions (let's say Claude's 100/month) to a median developer salary (let's
by lluisantoni 2mo ago
There is something I have been pondering recently. If we compare the cost of AI subscriptions (let's say Claude's 100/month) to a median developer salary (let's say 100k/year to 200k/year), the difference is orders of magnitude. This fills like a gap that needs to close. I suspect llms are too cheap right now but will raise their prices to a point where only big companies will be able to afford subscriptions to use them. I think soon we will see models that are only sold at very high prices.
- terabytest 2mo agoLLMs are not as cheap on enterprise plans.
- lluisantoni 2mo agoAlso, something else to add. At first I thought no one wants to build data centers in hotter areas in the middle of deserts (many places in the American continent). So nobody would spend money building a data center in the Chihuahuan Desert for instance. However, a game of latencies will either require cover llm access from these areas, or make people move closer to the other data centers. In the former, llm prices will go up; in the latter, there will be a migration towards data centers that increase the price of the areas around.
- KeplerBoy 2mo agoWho cares about a few ms more latency on an LLM API? Maybe for voice, but most other use-cases are quite latency insensitive.
- goalieca 2mo agoYeah, the customer support use case is already grinding me even worse than offshoring to India.
- mythrwy 2mo agoThey are building data centers in the Chihuahuan Desert right now. Meta has a huge one planned right outside El Paso.
- cracell 2mo agoI don't understand this argument. Go to OpenRouter and look at all of the unsubsidized providers.
- KeplerBoy 2mo agoOpen weight models tell a different story. Inference is not that much more expensive than what a 100$ plan would allow and will only get cheaper (for current capability models of course, frontier not so much).
- lopis 2mo ago> 100k/year to 200k/year Is this range just Silicon Valley or what is this? Even including just Europe, you're looking at a lower bracket of 10k. If you expand to the rest of the world... Or do you think rich cities in the USA, where developers make 100k+ per year, can alone sustain this industry?
- ido 2mo agosalary cost to the company is a lot higher than gross salary (which itself is a lot higher than net salary). you can guestimate total salary cost to be about 1.5x gross salary, so for the lower bound: 100k / 1.5 = $66,666.67 = €57,813.34. €57-114k p.a. is well within the order of magnitude of yearly gross developer salaries in Western Europe (e.g. Germany).
- NoDodgeQuestion 2mo agoThis is something I have been pondering recently. If I compare the cost of a plunger ($23.99 on Amazon) to a median plumber salary ($62,970 per year per BLS), the difference is orders of magnitude. This feels like a gap that needs to close. I suspect plungers are too cheap right now but will raise their prices to a point where only big companies will be able to afford subscriptions to use them. I think soon we will seen plungers that are only sold at very high prices.
- blanched 2mo agoJust because you can mad-lib something that makes sense at the surface doesn’t make it insightful. How are plungers comparable to LLMs?
- dwaltrip 2mo agoThey are both products with multiple sellers competing on price. If one seller raises their price, people can switch to the other seller. You can't only look at how much "value" the buyer gets from the product. That's the mistake made by the original comment. You might ask "why don't all of the LLM providers just raise their prices?". That's called price fixing or collusion, and is generally illegal.
- DamnInteresting 2mo ago> I suspect llms are too cheap right now but will raise their prices to a point where only big companies will be able to afford subscriptions to use them. "A.I." == "Artificially Inexpensive"
- wookmaster 2mo agoWhy is this a gap that needs to close? Can you elaborate more than feelings? Right behind these big models are local inference with AMD/Apple having a great hardware start and a lot of local sized models making great progress.