I think we are going to look at the era between 2019-2025 as a very rare blip in the history of public AI access. Regardless of whether fears about Mythos end up being justified, the clear trend is
1. AI models are becoming better and better at causing massively disruptive effects, leaving up larger and larger liabilities, especially as laws and regulations are being passed/proposed which would put the responsibility of some mass disruption/hacking event on the company which serves the model that made it possible
2. The relative advantage of serving an AI model for inference in exchange for money is waning compared to the advantage of using that model internally for purposes which accrue money/power/leverage for that AI company. Why serve a model at 30 dollars/million tokens when you've discovered you can use that model to run a simulated Quant firm with a net profit of 300 dollars/million tokens? Why offer the model to companies so they can find zero-day exploits, when you can find them yourself and sell the discovery to companies which would may millions to avoid this exploit being taken advantage of?
3. Why serve models so another wrapper company like Cursor can make billions off your tokens, and then try to train their own models as fast as possible, trained on your outputs so they aren't dependent on you? The entire AI startup industry and like 90% of YC batches depend on being able to serve frontier models at a profit, mediated through some wrapper, why can't OpenAI/ANthropic, once their models are good enough to handle the ideation/organizational problem, become their own incubator for thousands of AI run startups, running on models way better than the public has access to?
As a consequence, there is less and less incentive over time to offer models as an API to the public.