It’s been their mission to achieve AGI. This is what they sold. 
I agree. It seems like OpenAI has given us the tools to start with a smart model, and then distill it down to what we actually need. Why bother though 
I’ve been very impressed with Gemini Flash. I have not been impressed with not knowing how much they cost.
I also agree that small models are the future. They need to be contained, & somewhat predictable. There’s truly an art to applying LLMs that nobody bothers to respect. It’s just a magic block box to most people. LLM as the main feature is the curse of businesses. They serve much better as building blocks to systems.
That’s as a developer.
As a consumer, I can see the appeal in having an all-powerful model that I can use for day-to-day tasks through a proprietary interface. I would be very surprised if most companies don’t end up with some sort of subscription to this type of service, and have it contain all of their documents.
It leads me wondering how RAG systems will function in the future, and how tightly intertwined they will be with these services. One of my biggest hard-learned lessons working alongside companies like OpenAI is that building systems that augment their models is almost always a fool’s game. It’s building structures on moving sand. But, this may be a rapidly decaying truth if it’s believed that we have hit the wall of “general-purpose models” like GPT.
And how steerable will it be?
Throughout all this time I have noticed a decline in steerability with models. I have noticed this from other reports as well. These benchmarks enforce a “single-shot” method where it’s “all-or-nothing”. It’s moving people into a destroy and rebuild mentality. Complete waste.
I imagine this is why it’s kept as a “reasoning tool” and not a main model. It does make sense that it should be used as such for one-off operations.