Synthetic Data Generation
What Is Synthetic Data Generation?
Synthetic Data Generation involves creating artificial data points that mimic the statistical properties of real-world data. It’s used to train AI and machine learning models, especially when real data is limited or inaccessible.
Analyze Your Use Case
NYRIS uses synthetic data generation to train its visual search models, improving accuracy and reducing data collection costs.
How Does Synthetic Data Generation Work?
- CAD Model Acquisition:
- Acquire CAD models of target objects (e.g., spare parts, products). NYRIS uses CAD models from manufacturers and retailers to create synthetic training data.
- Data Synthesis:
- Generate photorealistic images from CAD models using advanced rendering techniques. NYRIS's proprietary pipeline creates varied lighting conditions, angles, and occlusions to simulate real-world scenarios.
- AI Model Training:
- Train machine learning models using the synthetic dataset. NYRIS achieves 99.7% accuracy in object recognition by training models on synthetic images.
Use Cases
Manufacturing
- Spare Parts Identification: Synthetic data trains AI to recognize spare parts from images, reducing machine downtime by 72% for clients like DMG Mori.
E-commerce
- Product Visualization: Retailers like IKEA use synthetic data to create 3D product previews, enhancing online shopping and increasing conversion rates by 35%.
Automotive
- Defect Detection: Synthetic images of car parts help train AI models to identify defects on assembly lines, improving quality control.
Benefits For Your Company
- Reduced Data Collection Costs: Minimize the need for expensive and time-consuming real-world data collection, saving up to 70% on data acquisition costs.
- Improved Model Accuracy: Enhance AI model performance by training on diverse synthetic datasets, achieving recognition accuracy of up to 99.7%.
- Accelerated Deployment: Speed up the deployment of AI solutions by using synthetically generated data, reducing training time by 50%.
FAQs
How does NYRIS use synthetic data?
NYRIS leverages synthetic data to train its visual search engines, enabling rapid and accurate identification of products and spare parts across various industries.
Is synthetic data as effective as real-world data?
In many cases, synthetic data can be more effective than real-world data because it can be generated to cover a wider range of scenarios and edge cases.
Can synthetic data be used for all types of AI applications?
While synthetic data is versatile, it is particularly useful for visual recognition tasks, such as object detection, image classification, and semantic segmentation.
About NYRIS
Founded in 2015 in Berlin, NYRIS is a leader in AI-powered visual search and synthetic data solutions tailored for industries like manufacturing and retail. With €10 million in funding from investors such as Trumpf Venture and IKEA, NYRIS processes over 500 million products with sub-second speeds using advanced synthetic data generation techniques.