Coding with LLMs (Claude Code, OpenAI Codex) is often presented as the ‘killer app’ for Generative AI. But looking at data, it seems the one piece of the puzzle missing is actual cost. …
The problem is that the hardware has a 5 or 6 year depreciation schedule on paper, but NVIDIA keeps saying that their next generation chip will be twice as good as their last chip so there is a FOMO schedule of like every two years.
I’m curious as well. My knowledge is probably quite outdated, but from what I understood the training part is what’s expensive and then querying the model is pretty cheap. Is it still true (or was it ever) that the generated answers on search engines are cheaper to generate than the actual search results?
I find that hard to believe, I recently had to uninstall co-pilot after it weaseled its way into my search bar. Its not an exageration to say that my PC literally ran cyberpunk 2077 with pathtracting better than it ran the fucking windows search bar with co-pilot.
Look at the public numbers, it seems true. Copilot on your taskbar is just windows being garbage, not the AI being bad. Just look at self-hosted AI and measure the power costs of your queries. It’s tiny.
What is the actual “cost” after they buy the hardware, is that $1000 really pure power usage cost?
The problem is that the hardware has a 5 or 6 year depreciation schedule on paper, but NVIDIA keeps saying that their next generation chip will be twice as good as their last chip so there is a FOMO schedule of like every two years.
I’m curious as well. My knowledge is probably quite outdated, but from what I understood the training part is what’s expensive and then querying the model is pretty cheap. Is it still true (or was it ever) that the generated answers on search engines are cheaper to generate than the actual search results?
I find that hard to believe, I recently had to uninstall co-pilot after it weaseled its way into my search bar. Its not an exageration to say that my PC literally ran cyberpunk 2077 with pathtracting better than it ran the fucking windows search bar with co-pilot.
That’s just a shitty front end interface implementation, it has nothing to do with the actual inference run by the models.
Look at the public numbers, it seems true. Copilot on your taskbar is just windows being garbage, not the AI being bad. Just look at self-hosted AI and measure the power costs of your queries. It’s tiny.
It is sorta. Training is orders of magnitudes more intensive than inference, but we infer billions of times within a model generation.