Simplify text analytics using AI with AWS and Teradata

During this event, you’ll learn how to accelerate text analytics with teradatagenai, a Python library that brings in-database AI capabilities to Teradata VantageCloud on Amazon Web Services (AWS). See how you can apply language models (LMs) and large language models (LLMs) to unstructured data quickly and securely—reducing the need for data movement while boosting scalability and performance. Organizations often struggle to extract insights from unstructured data when relying on manual processes, fragmented tools, or complex infrastructure. Teradatagenai simplifies gen AI text analytics by enabling secure, in-database processing of unstructured data—such as PDFs, emails, and transcripts—with flexible model options from Hugging Face and Amazon Bedrock. In this event, you’ll see how you can streamline text analytics workflows, reduce operational overhead, and unlock AI-driven insights faster—without moving data. • Deploy Hugging Face and Amazon Bedrock models using the TeradataAI() class to simplify model integration and accelerate gen AI workflows. • Apply diverse text analytics tasks—including sentiment analysis, classification, entity recognition, and personally identifiable information (PII) masking—directly within your database. • Reduce complexity and operational costs by minimizing data movement and leveraging GPU acceleration inside the analytics environment. Register now to not miss out!