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Edge AI

On-device AI and cloud models are used together. Apple's 2026 design uses both and sends the more demanding work to cloud models. Where a task should run depends on quality, memory, response time, energy use and privacy.

medium conviction growth

Research snapshot · updated Nov 12, 2026

State of the art (2026)

Phones and PCs now run useful AI models on the device, and send harder tasks to cloud models. Microsoft requires a neural processor rated at 40 TOPS or more for a Copilot+ PC, and its own Surface models list Intel processors rated at 40 or 48 TOPS. TOPS figures are a rough guide only, because they depend on numerical precision and workload. Apple uses both on-device and cloud models and keeps the more demanding work for the cloud. Where a task runs depends on quality, memory, latency, energy use and privacy.

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Signal stack

Evidence stacked leading → lagging

11 signals
talent
research
patent
expert
operational
market

Technology-native KPIs

Metrics that predict trajectory, tracked over time

4 tracked
Edge Inference Latency
Edge AI Chip Shipments
Edge AI Market Size
On-Device Model Parameters

Landscape map

Who builds what, and who depends on whom

87 players · 6 layers

Catalyst calendar

Dated events that will move the position

7 ahead

Technology roadmap

Milestones on the path to maturity

8 milestones

Watchlists

Companies, people and papers, each with a condition for removing it

20 · 20
Companies · 20
People · 20

Decision frameworks

What our view means for your job

Locked
Public Equity
PE / VC
Corporate Leader

Thesis changelog

When our view changed, and why

8 updates

Change our mind

2 disconfirming conditions

You've read the verdict. The file is much deeper.

The full signal stack, technology-native KPIs tracked over time, the landscape of who depends on whom, the dated catalyst calendar, decision frameworks for every desk, live watchlists and a record of every time our view on Edge AI has changed. All of it is in CanaryIQ.