AI has normalized single 9's of availability, even for non-AI companies such as Github that have to rapidly adapt to AI aided scaleups in patterns of use. Understandably, because GPU capacity is pre-allocated months to years in advance, in large discrete chunks to either inference or training, with a modest buffer that exists mainly so you can cannibalize experimental research jobs during spikes. It's just not financially viable to have spades of reserve capacity. These days in particular when supply chains are already under great strain and we're starting to be bottlenecked on chip production. And if they got around it by serving a quantized or otherwise ablated model (a common strategy in some instances), all the new people would be disappointed and it would damage trust.

Less 9's are a reasonable tradeoff for the ability to ship AI to everyone I suppose. That's one way to prove the technology isn't reliable enough to be shipped into autonomous kill chains just yet lol.