Synthetic Data
Synthetic Data vs Data Masking: Benefits & Challenges in 2024
Protecting sensitive data with the correct solution from insider threats is critical in many areas, including healthcare, finance, and government. Further than their immeasurable destruction to the confidentiality of customers and thus to the reputation of the businesses, data breaches in these sectors can also be extremely costly.
Synthetic Data vs Real Data: Benefits, Challenges in 2024
In recent years, there has been a growing interest in the use of synthetic data for various applications, such as machine learning and data analytics. According to Gartner, by 2030, synthetic data use will outweigh real data in AI models.
Synthetic Data Tools Selection Guide & Top 7 Vendors in 2024
As data-centric approaches gain prominence in AI/ML development, the use of synthetic data tools is expected to become more common. A survey of 300 computer vision specialists has shown %96 of them already using synthetic data.
Synthetic Data for Computer Vision: Benefits & Examples in 2024
Advancements in deep learning techniques have paved the way for successful computer vision and image recognition applications in fields such as automotive, healthcare, and security. Computers that can derive meaningful information from visual data enable numerous applications such as self-driving cars and highly accurate detection of diseases.
Synthetic Data for Healthcare: Benefits & Case Studies in 2024
From robot-assisted surgeries to medical imaging techniques, artificial intelligence applications in healthcare are rapidly changing the healthcare industry and providing improvements in cost and quality of service. For example, Accenture states that AI clinical health applications can create $150 billion annual savings for the US healthcare industry by 2026.
Top 20 Synthetic Data in 2024: 20 Use Cases & Applications
Synthetic data, also called artificially generated data, provides solutions for problems often encountered in data science applications such as data privacy and small data size. We listed the capabilities and most common use cases of synthetic data in different industries and departments/business units.
Synthetic Data in Finance: Top 4 Applications in 2024
Artificial intelligence has a diverse set of applications in financial services from process automation to chatbots and fraud detection. The estimates show that aggregate potential cost savings for banks from AI applications would be $447 billion by 2023.
Generative Adversarial Networks (GAN) & Synthetic Data [2024]
Generative Adversarial Network (GAN) is a type of generative model based on deep neural networks. You may have heard of it as the algorithm behind the artificially created portrait painting, Edmond de Bellamy, which was sold for $432,500 in 2018.
Synthetic Data to Improve Deep Learning Models in 2024
Despite its success in a wide range of tasks, deep learning has an important limitation: its data-hungry nature. Collecting and labeling huge data with desired properties is costly, time-consuming, or unfeasible in some applications. Synthetic data, also called artificially generated data, can help improve the performance of deep learning algorithms by meeting their data demands.
Synthetic Data Statistics: Benefits, Vendors, Market Size [2024]
Synthetic data generation tools generate synthetic data to preserve the privacy of data, to test systems or to create training data for machine learning algorithms. For more detailed information about synthetic data, please check our ultimate guide to synthetic data.