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Explaining complex information to patients

Ehud Reiter

Around 20 years ago, I was asked for a long-term “grand challenge” vision, and suggested building systems that helped members of the public understand complex information about themselves, especially medical information. Now that I’m in the last phase of my career (I’m 63.5

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Fantasy Football trades: How IBM Granite foundation models drive personalized explainability for millions

IBM Journey to AI blog

Fantasy football team owners are faced with complex decisions and an ocean of information. For the last 8 years, IBM has worked closely with ESPN to infuse its fantasy football experience with insights that help fantasy owners of all skill levels make more informed decisions.

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Generative AI in the Healthcare Industry Needs a Dose of Explainability

Unite.AI

Increasingly though, large datasets and the muddled pathways by which AI models generate their outputs are obscuring the explainability that hospitals and healthcare providers require to trace and prevent potential inaccuracies. In this context, explainability refers to the ability to understand any given LLM’s logic pathways.

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NeRFs Explained: Goodbye Photogrammetry?

PyImageSearch

Home Table of Contents NeRFs Explained: Goodbye Photogrammetry? Block #A: We Begin with a 5D Input Block #B: The Neural Network and Its Output Block #C: Volumetric Rendering The NeRF Problem and Evolutions Summary and Next Steps Next Steps Citation Information NeRFs Explained: Goodbye Photogrammetry? How Do NeRFs Work?

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How to Package and Price Embedded Analytics

This framework explains how application enhancements can extend your product offerings. Just by embedding analytics, application owners can charge 24% more for their product. How much value could you add? Brought to you by Logi Analytics.

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AI’s Got Some Explaining to Do

Towards AI

Yet, for all their sophistication, they often can’t explain their choices — this lack of transparency isn’t just frustrating — it’s increasingly problematic as AI becomes more integrated into critical areas of our lives. Enter Explainable AI (XAI), a field dedicated to making AI’s decision-making process more transparent and understandable.

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easy-explain: Explainable AI for YoloV8

Towards AI

(Left) Photo by Pawel Czerwinski on Unsplash U+007C (Right) Unsplash Image adjusted by the showcased algorithm Introduction It’s been a while since I created this package ‘easy-explain’ and published on Pypi. A few weeks ago, I needed an explainability algorithm for a YoloV8 model. The truth is, I couldn’t find anything.