#sr117 — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #sr117, aggregated by home.social.
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The Architecture Decisions CAIOs Cannot Delegate to Engineering
Architecture decisions, batch versus online prediction, cloud versus edge, offline versus online learning, coupled versus decoupled models. determine whether an AI system scales safely or collapses under real-world use. CAIOs and architects who get these trade-offs wrong don't get bad models; they get expensive rebuilds, stale predictions, or systems that optimize for outrage instead of value. -
The Architecture Decisions CAIOs Cannot Delegate to Engineering
Architecture decisions, batch versus online prediction, cloud versus edge, offline versus online learning, coupled versus decoupled models. determine whether an AI system scales safely or collapses under real-world use. CAIOs and architects who get these trade-offs wrong don't get bad models; they get expensive rebuilds, stale predictions, or systems that optimize for outrage instead of value. -
The Architecture Decisions CAIOs Cannot Delegate to Engineering
Architecture decisions, batch versus online prediction, cloud versus edge, offline versus online learning, coupled versus decoupled models. determine whether an AI system scales safely or collapses under real-world use. CAIOs and architects who get these trade-offs wrong don't get bad models; they get expensive rebuilds, stale predictions, or systems that optimize for outrage instead of value. -
The Architecture Decisions CAIOs Cannot Delegate to Engineering
Architecture decisions, batch versus online prediction, cloud versus edge, offline versus online learning, coupled versus decoupled models. determine whether an AI system scales safely or collapses under real-world use. CAIOs and architects who get these trade-offs wrong don't get bad models; they get expensive rebuilds, stale predictions, or systems that optimize for outrage instead of value. -
The Architecture Decisions CAIOs Cannot Delegate to Engineering
Architecture decisions, batch versus online prediction, cloud versus edge, offline versus online learning, coupled versus decoupled models. determine whether an AI system scales safely or collapses under real-world use. CAIOs and architects who get these trade-offs wrong don't get bad models; they get expensive rebuilds, stale predictions, or systems that optimize for outrage instead of value.