Viewing profile — hyunsoo90

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

Thank you for the interest! We have a team of ~50 in-house annotators that use our AI tools and we are looking to expand out to Southeast Asia, namely Vietnam or the Philippines, t…

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 als…

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 wor…

Thank you so much! The human-in-the-loop piece really starts to kick in for larger volumes of data where we can iterate the fine-tuning process several times. As an example, we wer…

Thanks for pointing this out. Although using crowdsourced labor could be the most cost-effective, we don't think it can guarantee the level of quality we get from in-house team. We…

Great question! Our AI is trained specifically for data annotation and that leads to a few differences. For example, our data annotation pipeline is not "end-to-end" and would not …

Thank you! Scale is doing great especially in the autonomous vehicles vertical. We are different in a few ways from Scale or other data annotation companies -- one, we really focus…

Hi HN, I’m Hyun, one of the co-founders of Superb AI ( https://www.superb-ai.com ) in the YC W19 batch. We use AI to semi-automatically collect and label training data for tech com…