article thumbnail

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.

article thumbnail

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.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

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.

article thumbnail

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.

article thumbnail

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.

AI 213
article thumbnail

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.

article thumbnail

Unstructured data management and governance using AWS AI/ML and analytics services

Flipboard

The first is the raw input data that gets ingested by source systems, the second is the output data that gets extracted from input data using AI, and the third is the metadata layer that maintains a relationship between them for data discovery.

ML 166