Obtaining Good Data: How to Improve Model Performance (1)
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With the advancement of artificial intelligence technology, various industries are making efforts to adopt AI. To meet the increasing demand for AI model development, large-scale data has become an essential requirement. Since data significantly influences the reliability and quality of AI systems, acquiring good data is considered a pressing challenge.
In response to this, governments around the world are making efforts to build and utilize data. However, the problem of data scarcity continues to be raised.
Obtaining good data is difficult.
Data transactions involve many considerations, making it the most challenging step for companies looking to buy or sell data. To activate such data transactions, the following obstacles need to be overcome:
- Obtaining high-quality data poses challenges, particularly from the supply side. The scarcity of processable raw data and the low quality of public data lead to limitations in data processing and analysis.
- Data traded from private providers often cannot be processed or utilized, resulting in an absolute scarcity of data. On the other hand, although public data is abundant, its quality is too low for practical use.
- Governments are strengthening their capacity for managing public data to address this low data quality issue. However, there is still much room for improvement in data processing and analysis.
- Introduction of the ‘2023 Public Data Quality Certification System’ in Korea
- Many companies face difficulties in selling their data.
- Even if there are suppliers who are willing to participate in data transactions, it is challenging to identify demanders who need the data, resulting in unsuccessful transactions.
- Due to the nature of data resources, demanders cannot gauge data quality, making it difficult to reach an agreement on data prices.
Secure good data with Cubig.
- Cubig transforms private companies’ data into synthetic data, enabling data processing and utilization. By leveraging Cubig’s proprietary synthetic data technology, it is possible to remove sensitive information from existing data and obtain high-quality data.
- Cubig can identify the demand for training datasets and match suppliers.
- Cubig can increase the utilization of data resources through the connection between suppliers and demanders.
Cubig acts as a mutual link in data transactions, transforming private companies’ data into fantastic synthetic data. This overcomes the quantity shortage of low-quality public data and the difficulty of processing private data while resolving obstacles in data transactions by matching demanders with suppliers. Cubig’s technology enhances the utilization of data resources like a wizard’s wand.
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