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Re-evaluating data management in the generative AI age

IBM Journey to AI blog

Generative AI has altered the tech industry by introducing new data risks, such as sensitive data leakage through large language models (LLMs), and driving an increase in requirements from regulatory bodies and governments.

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Unleashing the power of generative AI: Verisk’s Discovery Navigator revolutionizes medical record review

AWS Machine Learning Blog

At the forefront of harnessing cutting-edge technologies in the insurance sector such as generative artificial intelligence (AI), Verisk is committed to enhancing its clients’ operational efficiencies, productivity, and profitability. Discovery Navigator recently released automated generative AI record summarization capabilities.

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Why data governance is essential for enterprise AI

IBM Journey to AI blog

This problem is still being figured out by regulators, but it could easily become a major issue for any form of generative AI that learns from artistic intellectual property. We expect this will lead into major lawsuits in the future, and that will have to be mitigated by sufficiently monitoring the IP of any data used in training.

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Using Healthcare-Specific LLM’s for Data Discovery from Patient Notes & Stories

John Snow Labs

We will also review responsible and trustworthy AI practices that are critical to delivering these technology in a safe and secure manner. The post Using Healthcare-Specific LLM’s for Data Discovery from Patient Notes & Stories appeared first on John Snow Labs.

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A new era in BI: Overcoming low adoption to make smart decisions accessible for all

IBM Journey to AI blog

Emerging technologies such as generative AI (gen AI) are enhancing BI tools with capabilities that were once only available to data professionals. These tools are designed to guide users effortlessly from data discovery to actionable decision-making, enhancing their ability to act on insights with confidence.

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Hidden risk of shadow data and shadow AI leads to higher breach costs

IBM Journey to AI blog

The findings show some interesting trends that can help solve the data puzzle, including impacts to security, privacy, governance and regulation. All these aspects already see elevated risks rise from the rush to provision new generative AI (gen AI) initiatives and take them to market rapidly, leaving security considerations behind.

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AI that’s ready for business starts with data that’s ready for AI

IBM Journey to AI blog

By 2026, over 80% of enterprises will deploy AI APIs or generative AI applications. AI models and the data on which they’re trained and fine-tuned can elevate applications from generic to impactful, offering tangible value to customers and businesses.