Creating AI models has proven to simply be easier than other past innovations. Much lower barrier to entry, the knowledge seems to be spread pervasively within months of breakthroughs.
People seem to take offense at this idea, but the proof is in the pudding. Every week there's a new company with a new model coming out. What good did Google's "AI Talent" do for them when OpenAI leapfrogged them with only a few hundred people?
It's difficult to achieve high margins when barrier to entry is low. These AI companies are going to be moreso deflationary for society rather than high margin cash cows as the SaaS wave was
It's easier for large rich companies with infrastructure and datasets. It's very hard for small startups to build useful real world models from scratch, so you see most people building on top of SD and APIs, but that limits what you can build, for example it's very hard to build realistic photo editing on top of stable diffusion.
I wrote it from the perspective of a small startup (<10 people, bootstrapped or small funding). I think it's far cheaper and easier to build a nice competitive mobile app/saas than to build a really useful model.
But yes I agree, it will be very competitive with much smaller margins.
I've tried it, sure it's good, but not even close to the real thing. But yes it's getting cheaper through better hardware, better data and better architectures. Also it builds on Facebook's models that were trained for months on thousands of A100 GPUs.
People seem to take offense at this idea, but the proof is in the pudding. Every week there's a new company with a new model coming out. What good did Google's "AI Talent" do for them when OpenAI leapfrogged them with only a few hundred people?
It's difficult to achieve high margins when barrier to entry is low. These AI companies are going to be moreso deflationary for society rather than high margin cash cows as the SaaS wave was