@john @fromjason it would take serious technical analysis 😅 to sketch the space of possibilities, but my gut feeling is that if you remove the anxiety of building or defending trillion dollar valuations and focus on algorithms as lowly tools rather than pretend it's an impending superintelligence, then there is a lot of design space to explore about orchestrating computations (for the model building phase).

@john @fromjason no crystal ball but it seems there are still many uncertainties as to what architectures will be viable in the long term. The gigantic hyperconnected gpu datacenters reflect a breathless rush to develop as fast as possible, as large as possible LLM's, grabbing also all public content while nobody is watching. Literally move fast and break things, to create a captive user base etc. But is this sustainable and is it even needed for developing useful open models in the long run?

@john @fromjason famously "cloud" is just somebody else's Linux machine. A lot depends on who that somebody else is, what their business models, market power etc. If we condition on a world where three US conglomerates remain the only gatekeepers of any and all computing then "AI" is the least of our problems. The challenge is that the only challenge to this configuration comes from China. What is missing is a blueprint for democratic, widely distributed compute that is not a prop for oligarchy.