> Plan for a future where you can buy GPUs for ten cents on the dollar, where there's a buyer's market for hiring skilled applied statisticians, and where there

> Plan for a future where you can buy GPUs for ten cents on the dollar, where there's a buyer's market for hiring skilled applied statisticians, and where there's a ton of extremely promising open source models that have barely been optimized and have vast potential for improvement This doesn’t square entirely with the earlier claim that AI companies have (and will continue to have) “dogshit unit economics”. If you have a bunch of cheap “applied statistician” labor (kind of a reductive take, btw), cheap GPUs, and powerful open source models, it is a near certainty that companies would achieve favorable unit economics by optimizing existing models to run much more efficiently on existing GPUs. I happily pay $20/month for Google One to use Gemini 2.5 Pro. I don’t really need it to be a whole lot better. It’s a great product. If they can deliver inference of that level with positive margin (and keep it ad free), it’s a viable business. Investors will likely lose billions, if not trillions, but I don’t think the industry is inherently unprofitable - I just don’t think anybody has been incentivized to optimize for cost yet. Why would you, when investors continue to throw money at you to scale?