[jonghyuk0605]

Hi, I'm Jonghyuk, one of the co-founders. One point I would like to add is that a 90% accurate AI model may not be very useful for an application, but with the right data pipeline and well-designed system, we can extract quite a bit of boost out of it for data annotation.

[jeromebaek]

Numerically, how much is "quite a bit of a boost"?

[hyunsoo90]

It depends on how accurate our AI performs on a particular task, but as a back-of-the-envelope calculation, if we had a 90% accurate AI that means human annotators only have to work on the remaining 10%, giving us 10x boost. Obviously, there is some overhead not accounted for in this calculation, but with our current technology we can boost up to 10x depending on the type of data.

[treis]

How do you know which are the 90% it got wrong and which is the 10% it got right?

[hyunsoo90]

We have both AI-assisted and manual inspections in the pipeline. A good analogy would be an assembly line where humans and machines collaborate not only for building things but also for the quality control (ie. vision inspection system + manual inspection)

[thoughtstheseus]

Do other training data providers use ML/AI to do initial screens?

[hyunsoo90]

As far as I know, some do but most don't.