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Effective Learning Technologies

AI’s accuracy increases with more data for certain. However, preparing a lot of data is not an easy process, as providing accurate label information to data is a human task and requires effort and time.

In this case, if the AI provides information about what data is needed based on its current state, workers can work efficiently with fewer labeling tasks.

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Effective learning Technologies Information
Efficient AI learning using active learning



LAONPEOPLE uses outlier analysis technology to provide indicators to users to select helpful data for learning.
AI model’s reliability of judgment result can be estimated by analyzing previous learning on raw data.
The operator can evaluate the value of the data using this indicator.




These tasks lead to achieve the performance goals of the AI model efficiently through the following process.

1. Calculate the confidence using small data sets
2. Calculate the confidence of unlabeled data from the trained model
3. Data labeling priority: data with low confidence
4. Additional learning and improvement evaluation
5. The performance of the AI model is rapidly improved through the iterative process of 2~4.


The active learning technology provided by LAONPEOPLE can minimize the labeling work which is the most difficult task of an AI project,
and help to achieve high performance, this makes both cost and time required in entire project development reduced significantly.