Machine Learning

The Zynthetix platform leverages advanced machine learning models to provide high-quality synthetic data generation. This section provides an overview of the key machine learning technologies used in the platform.

RoBERTa

RoBERTa is an optimized version of the BERT model designed for natural language processing tasks. In Zynthetix, it is used for text categorization and classification.

Key Features

• Pretrained Model: Utilizes a pretrained model fine-tuned for specific tasks.
• Text Analysis: Analyzes and categorizes text inputs to identify data columns and categories.
• Scalability: Deployed on AWS SageMaker for scalable model training and inference.

GPT-NeoX

GPT-NeoX is a powerful language model used for generating high-quality synthetic text data. It is an open-source alternative to OpenAI's GPT-3.

Key Features

• Text Generation: Generates coherent and contextually relevant text based on input prompts.
• Custom Training: Can be fine-tuned on specific datasets for better performance.
• Scalability: Deployed on AWS EC2 instances with GPU acceleration for efficient processing.

StyleGAN3

StyleGAN3 is a state-of-the-art generative adversarial network (GAN) used for creating high-quality synthetic images.

Key Features

• Image Generation: Generates high-resolution and realistic synthetic images.
• Style Transfer: Allows for style mixing and transfer between images.
• Scalability: Deployed on AWS EC2 instances with GPU acceleration for efficient processing.

Custom Data Augmentation Model

The custom data augmentation model is designed to enhance existing datasets by generating additional synthetic data.

Key Features

• Data Augmentation: Generates additional rows of synthetic data based on existing datasets.
• Customizable: Can be tailored to specific data requirements and use cases.
• Scalability: Deployed on backend servers with cloud GPU instances for efficient processing.

By incorporating these advanced machine learning models, Zynthetix provides powerful tools for generating synthetic data tailored to specific user needs.