The Data Exchange with Ben Lorica AI Unlocked: The Data Bottleneck
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Jan 9, 2025 Generative AI is revolutionizing industries, but struggles with unstructured data create a significant bottleneck. Innovative tools are emerging to enhance data management and processing. As data shortages loom in 2025, the importance of high-quality data in model development becomes critical. Strategies like data curation and synthetic data are vital, alongside fostering strong partnerships, especially in regulated fields like finance and healthcare.
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AI-Centric Data Processing
- Generative AI requires AI-centric data processing.
- This handles diverse unstructured data like calls, PDFs, and videos, unlike SQL-centric systems.
Limitations of Current Data Tools
- Traditional data tools struggle with generative AI's heterogeneous workloads.
- Batch processing is sequential, while stream processing lacks flexibility for diverse data types.
RayData Success Stories
- RayData improves data processing by 3-8x for companies like ByteDance and Pinterest.
- It handles petabyte-scale audio and video datasets and optimizes recommender model training.