Unfortunately the competition is nipping at their heels so there's a good chance this blows up in their faces.
The problem is that today's AI companies have taken on so much funding that a reasonable, not crazy profit ratio isn't enough for them.
I kind of loathe the move away from a world where we could control our own computers and run our own software on them.
Someone has to pay the 7 trillion (the current projections for the AI datacenter build up)
To me the bigger takeaway is that these business are seeing massive volume in use and figuring out how to price the products accordingly.
With volume enterprises can already negotiate lower token rates. I don’t see a boiling the frog situation.
I think its assumed in the LLM model business that the models themselves are not a good moat, the next model by another company is just as likely to be as good as the current model. So companies like Anthropic have to tighten the noose slowly to start recovering their costs. This appears to be one of those steps.
Anthropic will also fail when the competition is.. near-equivalent-capability DeepSeek/Qwen/Llama on a $1k GPU with a break-even of 5 months of subscription costs. The value is simply not there for what they would need to charge to become profitable.
Lol no. Chinese AIs are definitely not "near-equivalent-capability". The empirical proof is pretty obvious: how many people have you heard talking about using their codex/claude code subscription vs their z.ai or qwen subscription? Moreover even the Chinese models require epic amounts of GPUs to run the full version, eg. https://apxml.com/models/glm-51 needs 1515 GB to run, and that's with a measly 1024 token context. To get it to run on your "$1k GPU" you'd need to quantize it, making it even dumber.
Uh, that’s a good thing
