Challenges in Data Production for AI with Human-in-the-Loop
2022
Today, successful Artificial Intelligence applications rely on three pillars: machine learning algorithms, hardware for running them, and data for training and evaluating models. Although algorithms and hardware have already become commodities, obtaining up-to-date and high-quality data at scale is still challenging-but possible by building hybrid human-computer pipelines called human-in-the-loop. This talk will show how to make a significant business impact using human-in-the-loop pipelines that combine machine learning with crowdsourcing. We will share the experience of one of the world's largest search engines, Yandex.
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
4
References
0
Citations
NaN
KQI