LLM architecture is about the model and machine learning workflows; cloud architecture is about the infrastructure that runs and supports applications ( including LLMs ). They're distinct but complementary.

The model can be trained and run locally. But for availability, fault tolerance, cost optimisation, security, compliance, multi-region deployment, observability.. cloud architecture is necessary.

A private cloud or on-premises infrastructure is the equivalent of a local cloud architecture. It can be done but is expensive to setup and to maintain. How do you find these threads? I always find something I didn't expect in them.

Since each biological-earth-life is like that of a fresh floppy disk (or empty USB-Drive) where «learning» re-starts from that of the human-baby biological-form and needing the floppy disk (or initially empty USB-Drive) to be filled with data for its particular «Avatar's» learning in its particular life-time my «learning» (like everyone else who hasn't «fallen» into the paradigm-locking trap of dogmatic-belief-systems) itself also continues to be on-going.

And the cognitive-load for me is already very high... such to the point where getting focused coherence can now often seem to take days of warm-up.

For this particular thread I was originally looking to see if any existed with the «synthetic» key-word (one does exist for this term) then decided to look-up «artificial» instead; several results showed up and I decided that it would be best to just go with the oldest-existing one which happened to be this one from before I had learned about the exists of these very forums themselves; this was after first going to the most-buried page worth of thread-titles for a bit of a review.

Time-Stamp: 030TL03m23d/11h57Z