Why zkML? Because @Microsoft has begun rolling out Copilot Local Actions — letting AI directly perform tasks on your device (system settings, file operations, app control, etc.).
Once the AI acts, not just suggests, the question changes:
How do we verify that the action matched the user’s intent?
2/
Local execution changes the trust model.
There are no server logs.
No external oversight layer.
The model interprets context → decides → executes.
You see the result, but not the reasoning.
And when reasoning is invisible, control becomes assumption.
3/
This is where zkML matters:
- Prove which model executed the action
- Prove the reasoning path followed defined policy
- Prove no unauthorized steps were taken
All without exposing internal state or system data.
4/
Imagine Copilot where:
✅Every automated action carries a verifiable execution trace
✅ Admins can audit behavior without accessing user content
✅ Users don’t need to “trust” AI — they can verify it behaved as intended
zkML turns automation from faith → to assurance.
5/
AI is becoming a system actor — not just an assistant.
When intelligence executes directly on the device, proof becomes the safety layer.
That’s what @PolyhedraZK is building: verifiable intelligence where action and intent stay aligned.
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