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AI & society2 sources · weekly

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MIT Technology Review

Smaller models are finding a durable place at the edge

New deployment patterns trade some general capability for privacy, lower latency, and predictable operating cost.

On-device inference is moving beyond demos Specialized models reduce serving overhead
4 source citations5 min read

3 new summariesSaved to AI & society

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Saved note · 5 min read

Why specialized AI models are moving closer to the user

Smaller systems are increasingly deployed where the data is created, reducing latency and limiting how much private information leaves the device.

What changes

The strongest use cases favor fast, bounded decisions over open-ended generation1, especially when network access is unreliable.

Source passage · 1

“On-device models can respond without sending the underlying data to a remote service…”

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