Veritone has launched Data Refinery, a new tool designed to transform unstructured data into AI-ready assets, addressing the growing challenge of data scarcity in artificial intelligence development.
Market context and critical need: The artificial intelligence industry faces a looming shortage of high-quality training data, with experts predicting a crisis as early as 2026.
- Industry analysts, including CB Insights, warn about the diminishing availability of accessible text data for AI training
- Organizations are struggling to process vast quantities of unstructured data into actionable insights
- Poor-quality or synthetic data can result in AI “hallucinations” – instances where systems generate inaccurate or nonsensical information
Core functionality and capabilities: Veritone Data Refinery converts unstructured data into structured formats suitable for advanced AI applications, including Large Language Models (LLMs) and Large Multimodal Models (LMMs).
- The platform processes various data types including text, audio, and images
- Built on Veritone’s aiWARE™ platform, the system unifies disparate data silos into a cohesive repository
- Organizations can use refined data internally or monetize it through licensing to third parties
Company expertise and track record: Veritone’s experience in data management demonstrates significant capability in handling large-scale information processing.
- In 2023, the company managed 11.38 petabytes of data
- Processed 64.5 million cognitive media hours for major clients including the NCAA
- Maintains strong security protocols with GDPR compliance and SOC2 certification
Expert perspectives: Industry leaders emphasize the importance of data processing capabilities in the current AI landscape.
- Dr. Christos Makridis, associate professor at Arizona State University and CEO of Dainamic, highlights the critical need for platforms that help organizations understand their unstructured data
- Ryan Steelberg, CEO of Veritone, emphasizes the company’s role in bridging the emerging gap in the AI ecosystem through secure and ethical data transformation
Strategic implications: The introduction of Data Refinery represents a significant development in addressing AI’s data challenges while raising important considerations about the future of AI development.
- The platform’s dual functionality for internal innovation and data monetization reflects evolving market needs
- Security and privacy features indicate growing awareness of data protection requirements
- The solution’s focus on high-quality data processing suggests a shift toward more reliable AI model training methods
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