The difference between local AI, edge AI and cloud AI
The three terms are used interchangeably and mean quite different things for latency, data control, energy and cost.
Marcus AdeyemiHardware engineer16 Jan 20265 min read
Local AI runs on hardware you control, usually on the same site as the people or systems using it. Edge AI is a broader term covering inference performed close to where data is produced, including embedded devices. Cloud AI runs in someone else's data centre against an API.
The useful distinctions are practical: who holds the data, what happens when connectivity drops, what the marginal cost per request is, and whose energy the work runs on.
Most credible deployments are hybrid. Local handles routine, private and latency-sensitive work; cloud absorbs peaks and workloads that need frontier-scale models.
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