There are huge advantages to labeling in-house such as quality control, faster iteration and privacy. New technologies like transfer learning, programmatic labeling and active learning are now making it practical for the best teams.

Data labeling is often the biggest bottleneck in machine learning. Active learning lets you train machine learning models with much less labeled data. The best AI-driven companies, like Tesla, use active learning.