Stu on Nostr: From my own experience scrubbing up the data quality is the secret sauce in all of ...
From my own experience scrubbing up the data quality is the secret sauce in all of this, I would take halving the anomalies v’s 25x volume in any training dataset.
But my point above is really about the application of AI. I still think generalisation is a mirage, you want 10^6 specialist models each deployed on 10^3 instances rather than 1 general model deployed 10^9 instances.
You get those specialists via automated data quality ops.
Automate the folks doing the automating.
Build a specialist forest instead of a monolith.
Then you have to workflow the specialists.
Then make it dynamic / self organising.
This is the path.
But my point above is really about the application of AI. I still think generalisation is a mirage, you want 10^6 specialist models each deployed on 10^3 instances rather than 1 general model deployed 10^9 instances.
You get those specialists via automated data quality ops.
Automate the folks doing the automating.
Build a specialist forest instead of a monolith.
Then you have to workflow the specialists.
Then make it dynamic / self organising.
This is the path.