Remove Healthcare Remove Structured Data Remove Unstructured Data
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Top Gen AI Use Cases: How to Turn Unstructured Data into Insights

Snowflake

Use cases range from getting immediate insights from unstructured data such as images, documents and videos, to automating routine tasks so you can focus on higher-value work. Gen AI makes this all easy and accessible because anyone in an enterprise can simply interact with data by using natural language.

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Accelerate AI Development with Snowflake

Snowflake

GPU-based model development and deployment: Build powerful, advanced ML models with your preferred Python packages on GPUs or CPUs serving them for inference in containers — all within the same platform as your governed data. Traditionally, SQL has been limited to structured data neatly organized in tables.

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Top 10 Data Engineering & AI Trends for 2025

Monte Carlo

Small data is the future of AI (Tomasz) 7. The lines are blurring for analysts and data engineers (Barr) 8. Synthetic data matters—but it comes at a cost (Tomasz) 9. The unstructured data stack will emerge (Barr) 10. But is synthetic data a long-term solution? Probably not. All that is about to change.

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Simplifying Multimodal Data Analysis with Snowflake Cortex AI

Snowflake

This major enhancement brings the power to analyze images and other unstructured data directly into Snowflakes query engine, using familiar SQL at scale. Unify your structured and unstructured data more efficiently and with less complexity. Introducing Cortex AI COMPLETE Multimodal , now in public preview.

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Top 10 Data & AI Trends for 2025

Towards Data Science

And over the last 24 months, an entire industry has evolved to service that very visionincluding companies like Tonic that generate synthetic structured data and Gretel that creates compliant data for regulated industries like finance and healthcare. But is synthetic data a long-term solution? Probablynot.

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Natural Language Processing in Healthcare: Using Text Analysis for Medical Documentation and Decision-Making

AltexSoft

Its deep learning natural language processing algorithm is best in class for alleviating clinical documentation burnout, which is one of the main problems of healthcare technology. Microsoft’s move tells a lot about the company’s (and the healthcare industry’s) priorities. Healthcare organizations generate a lot of text data.

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Top 20 Artificial Intelligence Project Ideas in 2023

Knowledge Hut

The development process may include tasks such as building and training machine learning models, data collection and cleaning, and testing and optimizing the final product. The privacy and security of patient data and ensuring that AI algorithms are accurate, dependable, and impartial must be overcome.

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