| For the near future it seems that the new models will consume whatever improved hardware capacity we have. Competing with that is challenging, but I also think there will be strong economic incentives towards cheaper but adequate models on other providers. I don't think we'll see home users being able to match even the low end clouds for a long time. Longer term I think we'll see these uses of AI cluster into a few groups: - maximal code / reasoning quality, at high prices (Fable) - typical code / agents (sub-Opus, Terra) - cheap but decent enough quality (think Deepseek / GLM / Luna) - so cheap I don't care about utilization (Deepseek, and friends) And also more niche ones: - ultra fast with high quality answers (typically sub-SOTA). Cerebras / dedicated silicon type approaches, expensive. - ultra fast with mostly-adequate answers, and an openness to retries, moving up to better models I think the open models will dominate (not with individuals, but low cost providers) all except the top 1-2 of those categories, and there will be a continuous erosion on the big player's moats. The top categories are also where all the money is, but I'm not sure it can justify those investments long-term. I also think they will have to squeeze more money out of them to justify the investments, which will also drive people down the list. Edit: clarifications. |
But they're not. Meta, SpaceX, Microsoft, Amazon, they're all leasing out capacity to others. If they were truly constrained, we wouldn't see that happening.