Thesis6 min read
Why AI's next era needs a personal intelligence layer
Every service that rebuilds a person's context creates another dependency. A persistent layer removes the need to rebuild it at all.
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Research5 min read
From centralized data to intelligence that learns with individuals
The first era learned from pooled records. The next level may require learning alongside a person whose record never moves.
Pooled data made general capability possible. It says less about what a system can do for one person over years, with a record that is continuous, permissioned and never handed over wholesale.
An open research question
If the personal record stays with the individual, learning has to reach the record rather than the record reaching the model. That raises questions about placement, permissions and provenance that are still being worked through.
- How does a system improve for a person without the personal record leaving their control?
- What evidence should accompany an answer so the person can see where it came from?
- How is scope expressed so an agent can act usefully and still stay inside it?
Prifina works on these questions with academic groups, including the Future Computing Group at the University of Oulu.
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