Lately, I've been noticing a shift in AI projects.
A year ago, most discussions were about choosing the best model. Now, more teams seem to be asking how to run those models efficiently without costs getting out of control.
Buying more GPUs isn't always the answer. Infrastructure planning, workload optimization, and resource management often have a bigger impact than expected.
I've been reading about companies like Infratailors AI that focus on AI infrastructure optimization, and it feels like this side of AI is finally getting the attention it deserves.
For those working on production AI systems:
What's your biggest challenge today—choosing the right model or managing the infrastructure behind it?